Wireless charging system for humanoid robot, and charging method therefor

Abstract

Provided in the present invention are a wireless charging system for a humanoid robot, and a charging method therefor. The charging system comprises a wireless charging mat consisting of a base mat, ferrites, wireless electromagnetic flux beam transmitting coils, pressure sensors, photoelectric sensors and visual beacons; and a vision camera and a wireless electromagnetic flux beam receiving converter which are arranged on a humanoid robot. The charging system further comprises a wireless communication server and a processor. When a humanoid robot is located on the wireless charging mat, the pressure sensors, the photoelectric sensors and the vision camera correspondingly acquire the real-time pressure, position and posture of the humanoid robot on the wireless charging mat, and information of a rechargeable battery of the humanoid robot, and after processing such information, the processor controls the switching, intensity and direction of electromagnetic current beam transmission for at least one wireless electromagnetic flux beam transmission unit which consists of a wireless electromagnetic flux beam transmitting coil and a ferrite and is near the wireless electromagnetic flux beam receiving converter, thereby realizing dynamic wireless charging under full operating conditions for the humanoid robot during standing or traveling operations.

Description

Humanoid robot wireless charging system and charging method Technical Field

[0001] This invention relates to a wireless charging system and its charging method, and more particularly to a wireless charging system and its charging method for a humanoid robot, belonging to the technical field of manufacturing and charging methods for wireless charging systems for humanoid robots. Background Technology

[0002] Humanoid robots, also known as humanoid robots, now generally refer to intelligent robots with a humanoid shape. Each of their movable joints is equipped with a servo motor, enabling them to swing their arms freely, walk autonomously, and perform various tasks autonomously.

[0003] With the development of technology, humanoid robot technology has made groundbreaking progress, and in the future, humanoid robots will play an increasingly important role in human production and life.

[0004] However, to date, humanoid robots are limited in size and therefore have a limited capacity to carry energy. As a result, they need to stop working periodically to replenish their energy, which affects their work efficiency.

[0005] In existing technologies, electric humanoid robots are the main form of humanoid robots, and their energy supply mainly relies on the batteries they carry. Among these, rechargeable batteries, such as rechargeable lithium batteries, are a mainstream form of power supply for existing electric humanoid robots. However, because rechargeable batteries, including lithium batteries, have low energy density, short battery life, and long charging times, humanoid robots powered by rechargeable batteries need to be recharged frequently in a short period of time, which seriously affects the operational efficiency of humanoid robots.

[0006] One approach to address this technical challenge is to increase the number or capacity of batteries carried by the humanoid robot to improve its endurance and reduce charging frequency. However, this method increases the construction and usage costs of the humanoid robot and reduces its flexibility. Furthermore, the increased weight also reduces energy efficiency. Moreover, the number or capacity of batteries carried by the humanoid robot cannot be increased indefinitely. Therefore, this method has limitations in improving endurance.

[0007] Fast charging is a technology that can effectively shorten the charging time of humanoid robots and is worth considering. However, this technology also has problems such as high cost, insufficient safety, high requirements for charging circuit capacity, and impact on battery life. Although fast charging technology helps reduce the charging time of humanoid robots and helps solve the battery life problem to some extent, it cannot completely solve the battery life problem and will drastically increase its production cost.

[0008] Using a charging cable to connect a humanoid robot for charging can effectively solve its battery life problem. This eliminates the need for the robot to stop working to recharge, improving its efficiency. However, a drawback is that the charging cable reduces the robot's flexibility and can easily become tangled, hindering its work process.

[0009] Wireless charging technology holds promise for solving this problem.

[0010] However, simply utilizing existing wireless charging technology still faces significant technical challenges because:

[0011] First, humanoid robots typically move continuously within a certain area during operation, which poses a significant challenge to existing wireless charging systems. Therefore, achieving efficient wireless charging for humanoid robots in operation has become a highly challenging technical problem, somewhat similar to refueling an aircraft in mid-air.

[0012] Secondly, when providing dynamic and efficient wireless charging services for humanoid robots in operation, it is necessary not only to consider not affecting the working process of the humanoid robot, but also to ensure the charging efficiency. At the same time, the development and manufacturing costs of the system equipment also need to be considered. Existing wireless charging technologies cannot perfectly solve these problems.

[0013] Furthermore, there is a technical challenge in dynamic wireless charging of humanoid robots under all working conditions: when the humanoid robot walks, the distance between the wireless charging receiver and the transmitter is constantly changing. When the receiver quickly approaches the wireless charging transmitter, the energy density it receives will increase rapidly according to electromagnetic laws. It is difficult for the wireless charging transmitter to reduce the transmission power in time. At this time, the receiving power of the wireless charging receiver will increase rapidly, which can easily damage the wireless charging receiver device. Summary of the Invention

[0014] To overcome the shortcomings of existing technologies, this invention provides a wireless charging system and method for humanoid robots, enabling dynamic and efficient wireless charging services for humanoid robots in all working conditions, whether standing or moving, thereby improving the robot's endurance and work efficiency and allowing it to play a greater role.

[0015] To this end, the present invention first provides a wireless charging system for humanoid robots, specifically including the following technical solutions:

[0016] A wireless charging system for humanoid robots, used for wireless charging of humanoid robots powered by rechargeable batteries while they are standing or moving during operation, wherein the humanoid robot has a charging interface for charging its rechargeable batteries, and the system includes:

[0017] The system includes a substrate, ferrite, a radio magnetofluid beam transmitting coil, a pressure sensor, a photoelectric sensor, a visual beacon, a visual camera, a radio magnetofluid beam receiver-converter, a wireless communication server, and a processor with a built-in artificial intelligence learning processing system, among which:

[0018] The base mat, ferrite, radio electromagnetic beam transmitting coil, pressure sensor, photoelectric sensor, and visual beacon constitute an integrated wireless charging mat. The base mat is used to lay on the area where the humanoid robot stands or moves. The ferrite is laid on the base mat. Multiple radio electromagnetic beam transmitting coils are embedded in the base mat, and each radio electromagnetic beam transmitting coil and its corresponding ferrite form a radio electromagnetic beam transmitting unit. Multiple pressure sensors are respectively arranged around or above the radio electromagnetic beam transmitting coils. Multiple photoelectric sensors and multiple visual beacons with different labels or shapes are respectively arranged on the base mat. The visual beacons with different labels or shapes are used to mark different areas of the wireless charging mat and the different environments in which it is located.

[0019] The visual camera and the wireless magnetocurrent receiver / converter are respectively mounted on the humanoid robot. The visual camera is a binocular wide-angle wearable stereo camera with a built-in rotating mechanism that can automatically adjust the shooting direction. The wireless magnetocurrent receiver / converter is equipped with a charging plug that can be matched with the charging interface of the humanoid robot. The visual camera, the wireless magnetocurrent receiver / converter, and the wireless charging blanket are also equipped with communication function modules and together form a wireless charging local area network with the wireless communication server. The wireless charging local area network is connected to and controlled by the processor. The pressure sensor and the photoelectric sensor are also connected to the processor.

[0020] When the humanoid robot steps onto the wireless charging mat, the pressure sensor, the photoelectric sensor, and the vision camera acquire real-time pressure information, photoelectric sensing information, position and posture, and surrounding environment image information of the humanoid robot on the wireless charging mat, respectively. Furthermore, the aforementioned information, along with the characteristic information of the humanoid robot's rechargeable battery, is transmitted to the processor via the wireless charging local area network. The processor, or a processor with an activated artificial intelligence learning processing system, processes this information and adjusts the electromagnetic beam emission switch, intensity, and direction of at least one of the nearest radio electromagnetic beam transmitting units of the radio electromagnetic beam receiver-converter mounted on the humanoid robot. The radio electromagnetic beam receiver-converter on the humanoid robot receives the electromagnetic beam emitted by the radio electromagnetic beam transmitting units and converts it into current to charge the humanoid robot's rechargeable battery.

[0021] Preferred:

[0022] The base blanket is made of a flexible flame-retardant polymer material, the ferrite is a flexible ferrite sheet, and the radio electromagnetic beam receiver converter is a wearable / removable shoe / boot-shaped radio electromagnetic beam receiver converter, which is worn / sleeved on the foot of the humanoid robot.

[0023] The shoe / boot-shaped radio electromagnetic beam receiver-converter includes a flexible polymer base, a flexible ferrite sheet fixed within the base, an electromagnetic beam receiving coil, a wireless communication device, and a microcontroller. The flexible ferrite sheet and the electromagnetic beam receiving coil together form a radio electromagnetic beam receiving unit. The wireless communication device is used for wireless communication of the shoe / boot-shaped radio electromagnetic beam receiver-converter, and the microcontroller is used for overall operation control of the shoe / boot-shaped radio electromagnetic beam receiver-converter.

[0024] Further:

[0025] Multiple pressure sensors, arranged around or above each of the wireless electromagnetic beam transmitting coils, are distributed in an orderly manner in a point-like manner, thereby forming a pressure sensing matrix corresponding to each of the wireless electromagnetic beam transmitting coils. The pressure sensing matrix is ​​used to acquire the pressure generated by the humanoid robot's feet on the wireless charging mat and its pressure distribution information and send it to the processor.

[0026] The multiple photoelectric sensors disposed on the base carpet are distributed in an orderly manner in a point-like form, thereby forming one or more photoelectric sensing matrices located on the base carpet. The photoelectric sensing matrices are used to acquire the spatial position information of the humanoid robot's feet on the wireless charging carpet, including the height difference between the feet and the wireless charging carpet and the projection position information of the feet on the wireless charging carpet, and send it to the processor.

[0027] The vision camera is worn on the head, neck or torso of the humanoid robot to acquire image information of the humanoid robot's feet, legs, arms, torso, visual beacons and working environment and send it to the processor;

[0028] The processor, or the processor with the artificial intelligence learning processing system enabled, determines the instantaneous foot position and overall posture of the humanoid robot relative to the wireless charging blanket based on the information acquired by the pressure sensor / pressure sensing matrix, the photoelectric sensor / photoelectric sensing matrix, and / or the vision camera, and predicts its next foot position and overall posture. This determines the instantaneous and next-next-next position and posture of the radio electromagnetic beam receiver-converter. Consequently, the processor controls the electromagnetic beam transmission switch, intensity, and direction of at least one radio electromagnetic beam transmitting unit near the instantaneous position of the radio electromagnetic beam receiver-converter of the humanoid robot, and prepares at least one radio electromagnetic beam transmitting unit corresponding to the radio electromagnetic beam receiver-converter for electromagnetic beam transmission switch, intensity, and direction control in the next moment.

[0029] Further:

[0030] The method by which the processor determines the instantaneous foot position and overall posture of the humanoid robot relative to the wireless charging blanket based on the information obtained by the pressure sensor / pressure sensing matrix, and predicts its next foot position and overall posture, specifically includes:

[0031] When the pressure sensor / pressure sensing matrix measures the pressure on the two feet of the humanoid robot and the pressure distribution information is consistent, the processor determines that the humanoid robot is standing at this moment. Then, by combining the position of the pressure sensor that detected the pressure with the humanoid robot's own weight, stride distance, work requirements and walking habits, the processor determines the instantaneous foot position and overall posture of the humanoid robot and predicts its foot position and overall posture in the next moment.

[0032] When the pressure sensor / pressure sensing matrix detects only the pressure of a single foot or the instantaneous pressure of both feet of the humanoid robot and its pressure distribution information, the processor first determines that the humanoid robot is moving. Then, the processor determines the position of the humanoid robot's feet based on the position of the pressure sensor that detected the pressure, and determines its direction of travel based on the pressure distribution information of the feet. Then, based on the humanoid robot's own weight, stride distance, and walking habits, combined with the previously determined foot positions and direction of travel, the processor determines the humanoid robot's instantaneous overall posture and predicts its next foot position and overall posture, wherein:

[0033] When the pressure sensor / pressure sensing matrix detects the instantaneous pressure of the humanoid robot's two feet and the pressure distribution information of each foot, the processor first determines the humanoid robot's raised foot and supporting foot at this moment. That is, the foot in the area where the pressure is continuously increasing is the humanoid robot's supporting foot, and the foot in the area where the pressure is continuously decreasing is the humanoid robot's raised foot.

[0034] Then, the processor combines the humanoid robot's own weight, stride distance, and walking habits to determine the humanoid robot's overall posture and predict its next foot position and overall posture.

[0035] Further:

[0036] The method by which the processor determines the instantaneous foot position and overall posture of the humanoid robot relative to the wireless charging blanket based on the information obtained by the photoelectric sensor / photoelectric sensing matrix, and predicts its next foot position and overall posture, specifically includes:

[0037] The processor determines the distance between the humanoid robot's feet and the wireless charging mat based on the time it receives the light feedback signal emitted by the photoelectric sensor / photoelectric induction matrix.

[0038] The processor determines the projection position of the humanoid robot's feet on the plane of the wireless charging mat based on the feedback signals of light emitted by photoelectric sensors at different positions in the photoelectric sensor / photoelectric induction matrix.

[0039] Based on the distance between the humanoid robot's feet and the wireless charging mat, and the projection position of the feet on the wireless charging mat's plane, the instantaneous spatial position of the feet is obtained. Combined with the humanoid robot's own size parameters and walking habits, the processor determines the humanoid robot's instantaneous foot position and overall posture, and predicts its next foot position and overall posture.

[0040] Further:

[0041] The method by which the processor determines the instantaneous foot position and overall posture of the humanoid robot relative to the wireless charging blanket based on the information acquired by the vision camera, and predicts the foot position and overall posture of the robot at the next moment, specifically includes:

[0042] First, the processor determines the instantaneous spatial distance and position between the humanoid robot's feet and the surface of the wireless charging blanket, as well as the overall posture of the humanoid robot, based on the three-dimensional image information of the humanoid robot's feet, legs, arms, torso, visual beacons, and working environment captured by the vision camera, as well as the image relationship between the feet and the surface of the wireless charging blanket.

[0043] Then, the processor combines the humanoid robot's own size, walking gait, and walking habit parameters to predict the position of its feet and overall posture at the next moment.

[0044] Further:

[0045] The specific method by which the processor determines the instantaneous foot position and overall posture of the humanoid robot relative to the wireless charging blanket and predicts its next foot position and overall posture based on the information acquired by the pressure sensor / pressure sensing matrix, the photoelectric sensor / photoelectric sensing matrix, and the vision camera includes:

[0046] First, information obtained from the pressure sensor / pressure sensing matrix is ​​used to determine the position of the humanoid robot's feet and its overall posture, and a trust score is given. Information obtained from the photoelectric sensor / photoelectric sensing matrix is ​​used to determine the distance between the humanoid robot's feet and the surface of the wireless charging mat, the projection position of the humanoid robot's feet on the surface of the wireless charging mat, and the overall posture of the humanoid robot, and a trust score is given. Information obtained from the vision camera is used to determine the overall posture of the humanoid robot and the spatial position of its feet, and a trust score is given. Wherein:

[0047] The determination results of the pressure sensor / pressure sensing matrix on the position of the humanoid robot's feet are assigned a reliability level based on a trust score, while the determination results on the overall posture of the humanoid robot are assigned a credibility level based on a trust score.

[0048] The determination results of the distance between the humanoid robot's feet and the surface of the wireless charging mat by the photoelectric sensor / photoelectric sensing matrix are rated as reliable based on the trust level; the determination results of the projection position of the humanoid robot's feet on the surface of the wireless charging mat are rated as reliable based on the trust level; and the determination results of the overall posture of the humanoid robot are rated as trustworthy based on the trust level.

[0049] The visual camera's determination of the humanoid robot's overall posture is rated as reliable based on a trust level score, while the determination of the humanoid robot's foot spatial position is rated as sub-reliable based on a trust level score.

[0050] Then, based on the aforementioned trust level rating, the reliability level information is used as the determination result, and the secondary reliability level and trustworthy level information are used as auxiliary references to give the evaluation results of the humanoid robot's instantaneous foot position and overall posture, and the prediction results of its foot position and overall posture at the next moment.

[0051] Further:

[0052] The specific method by which the processor of the artificial intelligence learning processing system determines the instantaneous foot position and overall posture of the humanoid robot relative to the wireless charging blanket and predicts its next foot position and overall posture based on the information acquired by the pressure sensor / pressure sensing matrix, the photoelectric sensor / photoelectric sensing matrix, and the vision camera includes:

[0053] First, the processor, which has activated the artificial intelligence learning and processing system, establishes and continuously improves its intelligent positioning model for determining and predicting the instantaneous and next-moment position and posture of the humanoid robot and its radio electromagnetic beam receiver converter relative to the wireless charging blanket by processing, learning, and autonomous relearning the information acquired by the pressure sensor / pressure sensing matrix, the photoelectric sensor / photoelectric sensing matrix and / or the vision camera, as well as the humanoid robot's own weight, size, walking gait and walking habit parameters.

[0054] Then, the artificial intelligence learning and processing system formulates in real time, based on the intelligent positioning model, the control rules for the processor to control the electromagnetic beam emission switch, intensity and direction of at least one of the radio electromagnetic beam transmitting units that are closest to the real-time location of the radio electromagnetic beam receiver converter of the humanoid robot. At the same time, it plans the preparatory rules for the at least one of the radio electromagnetic beam transmitting units corresponding to the radio electromagnetic beam receiver converter to prepare for the electromagnetic beam emission switch, intensity and direction control in the next moment.

[0055] Finally, the processor, based on the control rules and preparation rules formulated and planned by its artificial intelligence learning and processing system, and in conjunction with the real-time characteristic information of the rechargeable battery fed back by the radio electromagnetic beam receiver and converter, and the real-time working information of the radio electromagnetic beam receiver and converter, regulates the charging operation of the humanoid robot's rechargeable battery in the real-time state and prepares for the charging of the humanoid robot's rechargeable battery in the next state.

[0056] Based on any of the aforementioned humanoid robot wireless charging systems, this invention further provides a humanoid robot wireless charging method based on any of the aforementioned humanoid robot wireless charging systems, for dynamic wireless charging of a humanoid robot with a rechargeable battery as its power source and a charging interface in its standing or walking state, comprising the following steps:

[0057] In the area where the humanoid robot stands or walks, a wireless charging mat from any of the above-described humanoid robot wireless charging systems is laid out, and the visual camera and radio electromagnetic beam receiver converter from the humanoid robot wireless charging system are placed on the humanoid robot. The charging plug of the radio electromagnetic beam receiver converter is connected to the charging interface of the humanoid robot. Alternatively, multiple pressure sensors that are arranged in a dotted manner around or above each radio electromagnetic beam transmitting coil are grouped into a pressure sensing matrix, and multiple photoelectric sensors that are arranged in a dotted manner on the base mat are grouped into at least one photoelectric sensing matrix.

[0058] When the humanoid robot steps onto the wireless charging mat, the processor in the humanoid robot wireless charging system determines the instantaneous foot position and overall posture of the humanoid robot relative to the wireless charging mat based on the information obtained by the pressure sensor / pressure sensing matrix, the photoelectric sensor / photoelectric sensing matrix and / or the vision camera, and predicts its next foot position and overall posture.

[0059] Based on the determined instantaneous foot position and overall posture of the humanoid robot relative to the wireless charging mat, and the predicted foot position and overall posture of the humanoid robot in the next moment, the processor controls at least one of the radio electromagnetic beam transmitting units to perform electromagnetic beam transmission switching, intensity, and direction control through methods such as nearby directional transmission, pre-activated directional transmission, intelligent transmission by artificial intelligence learning processing system, and / or loss-prevention power transmission. This allows at least one of the radio electromagnetic beam transmitting units corresponding to the radio electromagnetic beam receiver converter in the next moment to prepare for electromagnetic beam transmission switching, intensity, and direction control, thereby enabling the radio electromagnetic beam receiver converter mounted on the humanoid robot to transmit an electromagnetic beam with controlled intensity and direction.

[0060] The wireless electromagnetic beam receiver-converter mounted on the humanoid robot receives the electromagnetic beam and converts it into current to charge the rechargeable battery. Simultaneously, the wireless electromagnetic beam receiver-converter transmits its real-time operating information and the real-time characteristic information of the rechargeable battery to the processor via the wireless charging local area network. The processor then adjusts and controls the transmission switch, intensity, and direction of the electromagnetic beam by the wireless electromagnetic beam transmitting unit, thereby enabling dynamic wireless charging of the humanoid robot in its standing or walking state. The real-time operating information of the wireless electromagnetic beam receiver-converter includes its current and voltage information, and the real-time characteristic information of the rechargeable battery includes its charge level.

[0061] Further:

[0062] The specific method by which the processor controls at least one of the radio electromagnetic beam transmitting units to perform electromagnetic beam emission switching, intensity, and direction control through the nearest-start directional emission method is as follows:

[0063] The processor determines the position of the radio electromagnetic beam receiver-converter based on the real-time foot position and overall posture of the humanoid robot, as well as the real-time operating information fed back by the electromagnetic beam receiver-converter and the real-time characteristic information of the rechargeable battery. It then controls one of the radio electromagnetic beam transmitting units or a radio electromagnetic beam transmitting array composed of multiple radio electromagnetic beam transmitting units on the wireless charging mat to transmit electromagnetic beams to the radio electromagnetic beam receiver-converter. This includes controlling the transmission switch, intensity, and direction of the electromagnetic beam, while keeping the remaining radio electromagnetic beam transmitting units or the radio electromagnetic beam transmitting array in a standby state with their operations suspended.

[0064] Further:

[0065] The specific method by which the processor controls at least one of the radio electromagnetic beam transmitting units to control the transmission switch, intensity, and direction of the electromagnetic beam through the pre-activated directional transmission mode is as follows:

[0066] The processor, based on the predicted foot position and overall posture of the humanoid robot, determines the position of the radio electromagnetic beam receiver-converter, along with the real-time operating information fed back by the radio electromagnetic beam receiver-converter and the real-time characteristic information of the rechargeable battery. It pre-activates and controls one radio electromagnetic beam transmitting unit or a phased array radio electromagnetic beam transmitting array composed of multiple radio electromagnetic beam transmitting units located near the radio electromagnetic beam receiver-converter. This enables the transmitter to emit electromagnetic beams to the radio electromagnetic beam receiver-converter that has just entered its electromagnetic beam emission range. The processor also controls the emission switch, intensity, and direction of the electromagnetic beams. Furthermore, it continuously adjusts the emission direction and intensity of the electromagnetic beams based on the trajectory of the radio electromagnetic beam receiver-converter and its real-time operating information, while keeping the remaining radio electromagnetic beam transmitting units or the radio electromagnetic beam transmitting array in a standby state.

[0067] Further:

[0068] The specific method by which the processor controls at least one of the radio electromagnetic beam transmitting units to perform electromagnetic beam emission switching, intensity, and direction control through the intelligent emission mode of the artificial intelligence learning and processing system is as follows:

[0069] The built-in artificial intelligence learning and processing system in the processor is activated, putting the processor into intelligent processor mode under the intelligent control of the artificial intelligence learning and processing system.

[0070] The intelligent processor, through its artificial intelligence learning and processing system's autonomous learning, correction, and relearning functions, processes and learns the information acquired by the pressure sensor / pressure sensing matrix, the photoelectric sensor / photoelectric sensing matrix, and / or the vision camera of the humanoid robot walking on the wireless charging mat. It also processes and learns the humanoid robot's own weight, size, gait, and walking habit parameters to establish and continuously improve an intelligent positioning model that determines the humanoid robot's instantaneous foot position and overall posture relative to the wireless charging mat, predicts its next foot position and overall posture, and thereby determines the instantaneous position and posture of the wireless magnetocurrent receiver converter and predicts its next position and posture.

[0071] After learning the humanoid robot's work actions, the intelligent positioning model can accurately predict the instantaneous foot position and overall posture of the humanoid robot relative to the wireless charging blanket at the next moment for repetitive tasks, identify motion data features from sensors, and then infer the action at the next moment.

[0072] When the humanoid robot steps onto the wireless charging mat, the intelligent processor processes the relevant information acquired by the pressure sensor / pressure sensing matrix, the photoelectric sensor / photoelectric sensing matrix, and / or the vision camera, and combines this information with the humanoid robot's own weight, size, gait, and walking habits parameters. Based on its intelligent positioning model, the processor determines the instantaneous position and attitude of the radio electromagnetic beam receiver converter and predicts its next position and attitude. Accordingly, it formulates control rules for switching, controlling the intensity and direction of electromagnetic beam emission at least one radio electromagnetic beam transmitting unit near the instantaneous position of the humanoid robot's radio electromagnetic beam receiver converter, and plans preparatory rules for at least one radio electromagnetic beam transmitting unit corresponding to the radio electromagnetic beam receiver converter to prepare for electromagnetic beam emission, intensity, and direction control in the next moment.

[0073] The intelligent processor, based on the control rules and preparation rules, as well as the real-time operating information fed back by the radio electromagnetic beam receiver-converter and the real-time characteristic information of the rechargeable battery, performs electromagnetic beam emission switching, intensity, and direction adjustment on at least one radio electromagnetic beam emitting unit or radio electromagnetic beam emitting array near the real-time location of the radio electromagnetic beam receiver-converter of the humanoid robot, and prepares at least one radio electromagnetic beam emitting unit corresponding to the radio electromagnetic beam receiver-converter to prepare for electromagnetic beam emission switching, intensity, and direction adjustment in the next moment, thereby realizing intelligent charging control of the rechargeable battery of the humanoid robot.

[0074] Further:

[0075] The specific method by which the processor controls at least one of the radio electromagnetic beam transmitting units to perform electromagnetic beam transmission switching, intensity, and direction control through the loss-prevention power transmission method is as follows:

[0076] When the processor cannot accurately predict the movement trajectory of the humanoid robot's feet, the wireless electromagnetic beam receiver-converter receives energy at a power level below its rated power.

[0077] When the humanoid robot's feet are far from the wireless charging mat, the processor controls the wireless charging transmitter or the wireless electromagnetic beam transmitter array to send electromagnetic beams, so that the receiving power of the wireless electromagnetic beam receiver is slightly lower than its rated value. This is to avoid the wireless charging transmitter or the wireless electromagnetic beam transmitter array not adjusting in time when the feet move downwards rapidly, which could cause overload damage to the wireless electromagnetic beam receiver.

[0078] When the processor detects that the humanoid robot's feet are approaching the wireless charging mat from a distance, the processor controls the wireless charging transmitter or the wireless electromagnetic beam transmitter array to gradually adjust the transmission power of the electromagnetic beam from a distance, so that the energy power received by the wireless electromagnetic beam receiver converter gradually approaches its rated value from a small to a large value.

[0079] When the processor detects that the humanoid robot's feet are close to the surface area of ​​the wireless charging mat, the processor controls the wireless charging transmitter or the wireless electromagnetic beam transmitter array to send an electromagnetic beam, so that the wireless electromagnetic beam receiver-converter can receive full load of energy for wireless charging.

[0080] When the processor can accurately and stably predict the movement trajectory of the humanoid robot's feet, based on the predicted foot position and overall posture of the humanoid robot, the processor determines the movement trajectory of the radio electromagnetic beam receiver-converter, along with the real-time operating information fed back by the radio electromagnetic beam receiver-converter and the real-time characteristic information of the rechargeable battery. It then pre-activates and controls one radio electromagnetic beam transmitting unit or a radio electromagnetic beam transmitting array composed of multiple radio electromagnetic beam transmitting units near the next position of the radio electromagnetic beam receiver-converter, preparing for the electromagnetic beam's transmission switch, intensity, and direction control. Wherein:

[0081] When the radio electromagnetic beam receiver converter mounted on the humanoid robot approaches the radio electromagnetic beam transmitter unit or the radio electromagnetic beam transmitter array from a distance, the processor adjusts the transmission pattern of the radio electromagnetic beam transmitter unit or the radio electromagnetic beam transmitter array in a timely manner according to the predicted movement trajectory of the radio electromagnetic beam receiver converter, so as to ensure that the receiving power of the radio electromagnetic beam receiver converter is always near the rated power.

[0082] When the radio electromagnetic beam receiver-converter mounted on the humanoid robot moves away from the radio electromagnetic beam transmitter unit or the radio electromagnetic beam transmitter array from near to far, the processor adjusts the transmission pattern of the radio electromagnetic beam transmitter unit or the radio electromagnetic beam transmitter array in a timely manner according to its predicted movement trajectory of the radio electromagnetic beam receiver-converter, so as to ensure that the receiving power of the radio electromagnetic beam receiver-converter is always near the rated power.

[0083] Compared with the prior art, the outstanding beneficial effects and significant progress of the present invention are as follows:

[0084] 1) The wireless charging system for humanoid robots provided by this invention has a wireless charging blanket that is an integrated component that combines a base blanket, ferrite, a radio electromagnetic beam transmitting coil, a pressure sensor, a photoelectric sensor, and a visual beacon. It has a compact structure, reasonable layout, and is easy to use and move. It can be laid in the area where the humanoid robot stands or moves to provide dynamic and efficient wireless charging services under all working conditions without affecting the original working mode of the humanoid robot. This greatly improves the endurance and working efficiency of the humanoid robot, allowing the humanoid robot to continuously exert its unique effectiveness.

[0085] Furthermore, when the wireless charging blanket is further optimized by using a flexible flame-retardant polymer material to make its base and a flexible ferrite, the resulting optimized wireless charging blanket can be bent and folded, which makes it more convenient to use, move and deploy and store.

[0086] 2) In the wireless charging system for humanoid robots provided by the present invention, the wireless electromagnetic beam receiver and converter is installed on the humanoid robot. Without affecting the operation of the humanoid robot, it can move with the humanoid robot, thereby facilitating dynamic and efficient wireless charging.

[0087] Furthermore, by further optimizing the wireless electromagnetic beam receiver and converter, specifically by designing it into a wearable / removable shoe / boot shape, the wireless electromagnetic beam receiver and converter with the shoe / boot shape can be easily worn / slipped onto the feet of the humanoid robot. In this way, it will not only not affect the movement and operation of the existing humanoid robot, but also make it easier to transmit dynamic electromagnetic beams under all working conditions through the wireless charging blanket, thereby realizing dynamic, efficient and wireless charging of the humanoid robot under all working conditions.

[0088] 3) The humanoid robot wireless charging system provided by this invention includes a wearable visual camera on the humanoid robot. The visual camera can effectively observe and record the real-time posture and movement of the humanoid robot, providing a good observation angle and high reliability. Therefore, the real-time position and posture of the humanoid robot can be accurately determined through visual observation, and its position and posture at the next moment can be predicted. This allows the position of the wireless electromagnetic beam receiver converter placed on the humanoid robot at the current moment and the predicted next moment to be determined, thereby enabling the wireless electromagnetic beam transmitting unit to transmit electromagnetic beams more efficiently and accurately, improving the charging efficiency of the humanoid robot.

[0089] 4) The humanoid robot wireless charging system provided by this invention includes not only a vision camera wearable on the humanoid robot, but also multiple pressure sensors and photoelectric sensors respectively disposed around or above the wireless magnetocurrent transmitting coil. Furthermore, the multiple pressure sensors and photoelectric sensors can also form a pressure sensing matrix and a photoelectric sensing matrix around or above the corresponding wireless magnetocurrent transmitting coil, thereby constituting an observation and measurement system for the real-time position and posture of the humanoid robot on the wireless charging mat, either individually or in combination. This provides a basis for the processor to determine and predict the real-time and next-time position and posture of the wireless magnetocurrent receiving converter, thereby ensuring efficient and accurate charging.

[0090] 5) The humanoid robot wireless charging system provided by this invention also forms a wireless charging local area network connected to the processor through a vision camera, a wireless magnetocurrent transmitting coil, a wireless magnetocurrent receiving converter, and a wireless communication server. Furthermore, pressure sensors and photoelectric sensors or pressure sensing matrix and photoelectric sensing matrix are connected to the processor, thereby forming an information transmission and processing system that can efficiently and timely acquire the real-time posture and position information of the humanoid robot on the wireless charging mat, as well as the charging information of the humanoid robot. This system can perform efficient, precise, and dynamic wireless charging of the humanoid robot's battery, thereby improving the humanoid robot's endurance and working efficiency, and allowing it to play a greater role.

[0091] 6) In the wireless charging system for humanoid robots provided by this invention, the processor also has a built-in artificial intelligence learning and processing system. Therefore, this invention can make full use of the powerful autonomous learning and modeling processing capabilities of the artificial intelligence learning and processing system. By obtaining the real-time posture and position information of the humanoid robot on the wireless charging mat and its charging information through the wireless charging local area network, and combining the humanoid robot's own weight, size, walking gait and walking habits, a positioning model is established to determine and predict the real-time and next-moment position and posture of the humanoid robot and its wireless electromagnetic beam receiver and converter relative to the wireless charging mat. The control rules for the electromagnetic beam emission switch, intensity and direction adjustment of the humanoid robot's wireless electromagnetic beam receiver and converter are planned in real time, so as to intelligently, efficiently and accurately control the charging of the humanoid robot's rechargeable battery.

[0092] Because the artificial intelligence learning processing system possesses powerful autonomous learning and modeling capabilities, it can learn from historical data related to the humanoid robot's overall posture and foot trajectory changes. This includes learning from detection data from pressure sensors / pressure sensing matrices, photoelectric sensors / photoelectric sensing matrices, and / or image data from vision cameras. Furthermore, it combines this learning with processing and learning of parameters such as the humanoid robot's weight, size, gait, and walking habits, and autonomous relearning, to establish a system that determines the humanoid robot's instantaneous foot position and overall posture relative to the wireless charging mat, predicts its next foot position and overall posture, and thereby determines the radio... The intelligent positioning model that uses magnetorheological beam receivers and converters to determine the instantaneous position and attitude of the robot and predict its next position and attitude is an intelligent model that combines rule-based and data learning. This model can be used to extract motion data related to humanoid robots. Since the tasks performed by humanoid robots are usually fixed, after a period of learning, this model can accurately judge and predict the posture and trajectory of humanoid robots. This is similar to how an intelligent agent can learn the entire set of actions of a humanoid robot and infer subsequent posture and trajectory based on current and previous motion characteristics, thus providing a guarantee for intelligent wireless charging of humanoid robots.

[0093] 7) This invention fully utilizes the aforementioned humanoid robot wireless charging system. Through methods such as proximity-based directional transmission, pre-initiated directional transmission, intelligent control of transmission via an artificial intelligence learning and processing system, and / or loss-prevention power transmission, or combinations of these methods as needed, it controls the transmission, intensity, and direction of the electromagnetic beam at the wireless electromagnetic beam receiver-converter in the immediate state. It also prepares at least one wireless electromagnetic beam transmitting unit corresponding to the wireless electromagnetic beam receiver-converter for electromagnetic beam transmission and intensity and direction control in the next moment. This provides a dynamic and efficient wireless charging method for humanoid robots in standing or moving operations, contributing to improved endurance and work efficiency, maximizing their utility, and ensuring the safety of the humanoid robot and its wireless charging system. It effectively prevents equipment overload damage and provides a novel technical solution for dynamic charging of humanoid robots under all working conditions. It achieves technical effects unattainable by existing technologies, possessing outstanding substantive features and significant progress, and is highly valuable for promotion and application. Attached Figure Description

[0094] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments of the present invention will be briefly introduced below.

[0095] Obviously, the accompanying drawings described below are only some of the drawings of the embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort, but these other drawings are also within the scope of the drawings required for the embodiments of the present invention.

[0096] Figure 1 is a schematic diagram of the composition structure of a wireless charging system for a humanoid robot provided in an embodiment of the present invention;

[0097] Figure 2 is a schematic diagram of the pressure sensing matrix structure of a humanoid robot wireless charging system provided in an embodiment of the present invention.

[0098] Figure 3 is a schematic diagram of the photoelectric sensing matrix structure of a wireless charging system for a humanoid robot provided in an embodiment of the present invention.

[0099] Figure 4 is a schematic diagram of the shoe / boot sole structure of a shoe / boot-shaped wireless magnetocurrent receiver converter of a humanoid robot wireless charging system provided in an embodiment of the present invention.

[0100] In the picture:

[0101] 10 - Humanoid robots;

[0102] 100-Wireless charging blanket, 110-Base blanket, 120-Ferrite, 130-Radio electromagnetic beam transmitting coil, 141-Pressure sensor, 140-Pressure sensing matrix, 151-Photoelectric sensor, 150-Photoelectric sensing matrix, 160-Visual beacon;

[0103] 210-Vision camera, 220-Radio electromagnetic beam receiver-converter, 221-Substrate, 222-Ferrite sheet, 223-Electromagnetic beam receiving coil, 224-Wireless communication device, 225-Microcontroller, 230-Wireless communication server;

[0104] 300-processor. Detailed Implementation

[0105] To make the objectives, technical solutions, beneficial effects, and significant advancements of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings provided for the embodiments of the present invention. Obviously, all the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0106] It should be noted that the term "comprising" and any variations thereof in the specification and claims of this invention are intended to cover non-exclusive inclusion, for example, including not only a series of listed technical features and structural components, but also optionally technical features and structural components not listed, or optionally the connection relationships between these technical features and structural components.

[0107] It should be understood that in the description of the embodiments of the present invention, the terms "upper" and "lower" and other indicative directional or positional terms are used only based on the directional or positional relationships shown in the accompanying drawings of the embodiments of the present invention. They are used to facilitate the description of the embodiments of the present invention and to simplify the explanation, and are not intended to indicate or imply that the device or element must have a specific orientation, specific orientational structure and operation. Therefore, they should not be construed as limitations on the present invention.

[0108] In this invention, unless otherwise explicitly specified and limited, the terms "installation" and "setting" should be interpreted broadly. For example, they can refer to fixed installation or setting, detachable installation or setting, or movable installation or setting. They can also refer to an integral connection, direct connection or indirect connection through an intermediate medium, or internal communication between two structural elements or interaction between two elements. Unless otherwise explicitly limited, those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0109] It should also be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0110] The technical solution of the present invention will now be described in detail with reference to specific embodiments.

[0111] Example 1

[0112] This embodiment provides a wireless charging system for a humanoid robot powered by a rechargeable battery, which is used for wireless charging in its standing or walking operation. The humanoid robot has a charging interface for charging its rechargeable battery.

[0113] Figure 1 is a schematic diagram of the composition structure of a wireless charging system for a humanoid robot provided in an embodiment of the present invention:

[0114] A wireless charging system for a humanoid robot includes a substrate 110, a ferrite core 120, a radio electromagnetic beam transmitting coil 130, a pressure sensor 141, a photoelectric sensor 151, a visual beacon 160, a visual camera 210, a radio electromagnetic beam receiver / converter 220, a wireless communication server 230, and a processor 300 with a built-in artificial intelligence learning and processing system, wherein:

[0115] A wireless charging mat 100 is composed of a base mat 110, ferrite 120, a radio electromagnetic current transmitting coil 130, a pressure sensor 141, a photoelectric sensor 151, and a visual beacon 160. The base mat 110 is used to lay on the area where the humanoid robot 10 stands or moves. The ferrite 120 is laid on the base mat 110. Multiple radio electromagnetic current transmitting coils 130 are embedded in the base mat 110, and each radio electromagnetic current transmitting coil 130 and its corresponding ferrite 120 constitute a radio electromagnetic current transmitting unit. Multiple pressure sensors 141 are respectively arranged around or above the radio electromagnetic current transmitting coils 130. Multiple photoelectric sensors 151 and multiple visual beacons 160 with different labels or shapes are respectively arranged on the base mat 110. The visual beacons 160 with different labels or shapes are used to mark different areas of the wireless charging mat 100 and the different environments in which they are located.

[0116] The visual camera 210 and the wireless magnetocurrent receiver-converter 220 are respectively installed on the humanoid robot 10. The visual camera 210 is a binocular wide-angle wearable stereo camera with an internal rotating mechanism that can automatically adjust the shooting direction. The wireless magnetocurrent receiver-converter 220 is equipped with a charging plug that can be matched with the charging interface of the humanoid robot 10. The visual camera 210, the wireless magnetocurrent receiver-converter 220 and the wireless charging blanket 100 are also equipped with communication function modules and together form a wireless charging local area network with the wireless communication server 230. The wireless charging local area network is connected to and controlled by the processor 300. The pressure sensor 141 and the photoelectric sensor 151 are also connected to the processor 300.

[0117] When the humanoid robot 10 steps onto the wireless charging mat 100, the pressure sensor 141, photoelectric sensor 151, and vision camera 210 acquire real-time pressure information, photoelectric sensing information, position and posture, and surrounding environment image information of the humanoid robot 10 on the wireless charging mat 100, respectively. The above information, as well as the characteristic information of the humanoid robot 10's rechargeable battery (not shown in the figure), are also sent to the processor 300 through the wireless charging local area network. The processor 300, or the processor 300 with the artificial intelligence learning processing system enabled, processes this information and performs electromagnetic beam emission switching, intensity, and direction control operations on at least one nearby radio electromagnetic beam transmitting unit of the radio electromagnetic beam receiver-converter 220 placed on the humanoid robot 10. The radio electromagnetic beam receiver-converter 220 on the humanoid robot 10 receives the electromagnetic beam emitted by the radio electromagnetic beam transmitting unit and converts it into current to charge the humanoid robot 10's rechargeable battery (not shown in the figure).

[0118] From the above description, it can be seen that:

[0119] The humanoid robot wireless charging system provided in this embodiment is a device that includes a base blanket, ferrite, a radio electromagnetic beam transmitting coil, a pressure sensor, a photoelectric sensor, a visual beacon, a visual camera, a radio electromagnetic beam receiver-converter, a wireless communication server, and a processor. The base blanket, ferrite, radio electromagnetic beam transmitting coil, pressure sensor, photoelectric sensor, and visual beacon constitute an integrated wireless charging blanket. The processor also has a built-in artificial intelligence learning processing system (i.e., an AI system). The visual camera and radio electromagnetic beam receiver-converter are installed on the humanoid robot. Therefore, it can be seen that the wireless charging blanket is not only compact in structure, reasonable in layout, easy to use and move, but also can provide dynamic and efficient wireless charging services for existing humanoid robots that are powered by rechargeable batteries, without affecting the operation of the humanoid robot. This can greatly improve the battery life and work efficiency, allowing it to play a greater role.

[0120] Since the humanoid robot wireless charging system provided in this embodiment includes a vision camera, the real-time posture and movement of the humanoid robot can be observed well through the vision camera. It has a good observation angle and extremely high reliability. Therefore, judging the real-time position and posture of the humanoid robot and predicting its position and posture in the next moment through visual observation has extremely high accuracy and certain reliability. It can quickly and accurately determine the position of the humanoid robot and its wireless electromagnetic beam receiver and converter in the current moment and predict the next moment, so as to efficiently and accurately transmit electromagnetic beams, thereby improving the charging efficiency of the humanoid robot.

[0121] Furthermore, the humanoid robot wireless charging system provided in this embodiment also includes multiple pressure sensors and photoelectric sensors respectively disposed around or above the wireless magnetocurrent transmitting coil. These sensors, together with the vision camera, form a photoelectric, pressure, and visual observation and measurement system for the real-time position and posture of the humanoid robot on the wireless charging mat, either alone or in combination. This provides a reliable source of information and basis for the processor to determine and predict the real-time and next-moment position and posture of the humanoid robot and its wireless magnetocurrent receiving converter, further ensuring the high efficiency and accuracy of charging.

[0122] Meanwhile, in the humanoid robot wireless charging system provided in this embodiment, a visual camera, a wireless magnetocurrent transmitting coil, a wireless magnetocurrent receiving converter, and a wireless communication server are combined to form a wireless charging local area network connected to the processor. Pressure sensors and photoelectric sensors, or pressure sensing matrices and photoelectric sensing matrices, are also connected to the processor. This constitutes an information transmission and processing system that can efficiently and timely acquire the real-time posture and position information of the humanoid robot on the wireless charging mat, as well as the real-time power information of the humanoid robot's rechargeable battery. This enables efficient, precise, and dynamic charging of the humanoid robot's rechargeable battery, perfectly achieving the purpose of this invention: improving the endurance and working efficiency of the humanoid robot and allowing it to exert greater utility.

[0123] As a preferred embodiment, the humanoid robot wireless charging system provided in this example includes:

[0124] The base blanket 110 can be made of a flexible flame-retardant polymer material, the ferrite 120 can be made of a flexible ferrite sheet, and the radio electromagnetic beam receiver converter 220 can be designed as a slip-on / shoe-shaped radio electromagnetic beam receiver converter, and the slip-on / shoe-shaped radio electromagnetic beam receiver converter can be worn / sleeved on the foot of the humanoid robot 10.

[0125] Figure 4 is a schematic diagram of the shoe / boot sole structure of a shoe / boot-shaped wireless magnetocurrent receiver converter in a wireless charging system for a humanoid robot provided in an embodiment of the present invention.

[0126] The shoe / boot-shaped wireless electromagnetic beam receiver and converter has a shoe / boot sole plate including a flexible polymer base 221, a flexible ferrite sheet 222 fixed in the base 221, an electromagnetic beam receiving coil 223, a wireless communication device 224, and a microcontroller 225. The flexible ferrite sheet 222 and the electromagnetic beam receiving coil 223 together form a wireless electromagnetic beam receiving unit. The wireless communication device 224 is used for wireless communication of the shoe / boot-shaped wireless electromagnetic beam receiver and converter. The microcontroller 225 is used for the overall operation control of the shoe / boot-shaped wireless electromagnetic beam receiver and converter.

[0127] Obviously, through the above optimization process, namely, using a flexible flame-retardant polymer material to make the base blanket and adopting flexible ferrite, the resulting wireless charging blanket can be bent and folded, thus further facilitating its use, movement, and storage.

[0128] Furthermore, the optimized wireless electromagnetic beam receiver and converter, designed as a slip-on / boot shape, can be easily worn / slipped onto the feet of the humanoid robot. This not only does not affect the robot's operation and movement, but also allows for more convenient dynamic transmission of electromagnetic beams under all working conditions via a wireless charging pad, thereby achieving efficient, dynamic, and all-condition wireless charging for the humanoid robot.

[0129] Furthermore, as shown in Figures 1 and 2, which are schematic diagrams of the pressure sensing matrix structure of a humanoid robot wireless charging system provided in an embodiment of the present invention, and Figure 3, which is a schematic diagram of the photoelectric sensing matrix structure of a humanoid robot wireless charging system provided in an embodiment of the present invention:

[0130] Multiple pressure sensors 141 arranged around or above each wireless electromagnetic beam transmitting coil 130 are distributed in an orderly manner in a point-like manner, thereby forming a pressure sensing matrix 140 corresponding to each wireless electromagnetic beam transmitting coil 130. The pressure sensing matrix 140 is used to acquire the pressure generated by the humanoid robot 10's feet on the wireless charging mat 100 and its pressure distribution information and send it to the processor 300.

[0131] Multiple photoelectric sensors 151 disposed on the base blanket 110 are arranged in an orderly manner in a point-like form, thereby forming one or more photoelectric sensing matrices 150 on the base blanket 110. The photoelectric sensing matrices 150 are used to acquire the spatial position information of the humanoid robot 10's feet on the wireless charging blanket 100, including the height difference between the feet and the wireless charging blanket 100 and the projection position information of the feet on the wireless charging blanket 100, and send them to the processor 300.

[0132] The visual camera 210 is worn on the head, neck or torso of the humanoid robot 10 to acquire image information of the humanoid robot 10’s feet, legs, arms, torso, visual beacon 160 and working environment and send it to the processor 300.

[0133] The processor 300, or the processor 300 with the artificial intelligence learning processing system enabled, determines the instantaneous foot position and overall posture of the humanoid robot 10 relative to the wireless charging blanket 100 based on the information acquired by the pressure sensor 141 / pressure sensing matrix 140, the photoelectric sensor 151 / photoelectric sensing matrix 150, and / or the vision camera 210, and predicts its next foot position and overall posture. In this way, it determines the instantaneous and next-next ...

[0134] Clearly, arranging multiple pressure sensors and multiple photoelectric sensors in an orderly manner according to certain rules to form a pressure sensing matrix and a photoelectric sensing matrix respectively can more accurately and comprehensively obtain information such as the real-time pressure, pressure distribution, posture, position, and height difference between the humanoid robot's feet and the wireless charging mat surface. Together with a vision camera, this constitutes a more efficient, comprehensive, and accurate observation and measurement system for the humanoid robot's real-time position and posture on the wireless charging mat. This provides the processor with timely and accurate information to determine and predict the real-time and next-moment position and posture of the humanoid robot and the wireless magnetocurrent receiver-converter, ensuring efficient and precise charging.

[0135] Furthermore, the processor of the humanoid robot wireless charging system provided in this embodiment also includes an artificial intelligence learning processing system. The artificial intelligence learning processing system learns from the information acquired by the pressure sensor 141 and / or photoelectric sensor 151, vision camera 210 or pressure sensing matrix 140 and / or photoelectric sensing matrix 150, vision camera 210, and each of them, to establish a positioning model for determining and predicting the instantaneous and next-moment position and posture of the humanoid robot 10 and its radio electromagnetic beam receiver-converter 220 on the wireless charging mat 100. It also plans in real time the server to switch the electromagnetic beam emission and intensity control of at least one radio electromagnetic beam transmitting coil 130 near the instantaneous position of the humanoid robot 10 and its radio electromagnetic beam receiver-converter 220, and to prepare at least one radio electromagnetic beam transmitting coil 130 corresponding to the radio electromagnetic beam receiver-converter 220 for electromagnetic beam emission and intensity control in the next moment. Then, it uses the control rules to control the charging of the humanoid robot 10's rechargeable battery (not shown in the figure).

[0136] Clearly, this embodiment fully incorporates the achievements of existing artificial intelligence technology. Utilizing the powerful self-learning and modeling capabilities of the artificial intelligence learning and processing system, it acquires the real-time posture and position information of the humanoid robot on the wireless charging mat through the wireless charging local area network, as well as the real-time battery power information of the humanoid robot. Combined with parameters such as the humanoid robot's weight, size, gait, and walking habits, it establishes a positioning model that can determine and predict the real-time and next-moment position and posture of the humanoid robot and its wireless electromagnetic beam receiver converter on the wireless charging mat. This enables real-time planning of control rules for electromagnetic beam emission and intensity regulation of the humanoid robot's wireless electromagnetic beam receiver converter, thereby intelligently, efficiently, and accurately controlling the charging of the humanoid robot's battery.

[0137] To further aid in understanding the method by which the processor of the humanoid robot wireless charging system provided in the above embodiments determines the instantaneous position and posture of the humanoid robot on the wireless charging mat and predicts its next position and posture based on information acquired by the pressure sensor / pressure sensing matrix and / or electrical sensor / photoelectric sensing matrix and vision camera, will provide a detailed explanation below.

[0138] (1) The method by which the processor 300 determines the instantaneous foot position and overall posture of the humanoid robot 10 relative to the wireless charging blanket 100 based on the information obtained by the pressure sensor 141 / pressure sensing matrix 140 and predicts its next foot position and overall posture specifically includes:

[0139] When the pressure sensor 141 / pressure sensing matrix 140 measures the pressure on the two feet of the humanoid robot 10 and the pressure distribution information is consistent, the processor 300 determines that the humanoid robot 10 is standing at this moment. Then, combined with the position of the pressure sensor 141 that detected the pressure and the humanoid robot 10's own weight, stride distance, work requirements and walking habits, the processor determines the instantaneous foot position and overall posture of the humanoid robot 10 and predicts its foot position and overall posture in the next moment.

[0140] When pressure sensor 141 / pressure sensing matrix 140 detects only the pressure of a single foot or the instantaneous pressure of both feet of the humanoid robot 10 and its pressure distribution information, processor 300 first determines that the humanoid robot 10 is moving. Then, processor 300 determines the position of the humanoid robot 10's feet based on the position of the pressure sensor 141 that detected the pressure, and determines its direction of travel based on the pressure distribution information of the feet. Then, based on the humanoid robot 10's own weight, stride distance, and walking habits, combined with the previously determined foot position and direction of travel, processor 300 determines the instantaneous overall posture of the humanoid robot 10 and predicts its next foot position and overall posture, wherein:

[0141] When the pressure sensor 141 / pressure sensing matrix 140 detects the instantaneous pressure of the humanoid robot 10's two feet and the pressure distribution information of each foot, the processor 300 first determines the raised foot and supporting foot of the humanoid robot 10 at this moment. That is, the foot in the area where the pressure is constantly increasing is the supporting foot of the humanoid robot 10, and the foot in the area where the pressure is constantly decreasing is the raised foot of the humanoid robot 10.

[0142] Then, the processor 300 combines the humanoid robot 10's own weight, stride distance, and walking habits to determine the overall posture of the humanoid robot 10 and predict its next foot position and overall posture.

[0143] (2) The method by which the processor 300 determines the instantaneous foot position and overall posture of the humanoid robot 10 relative to the wireless charging blanket 100 based on the information obtained by the photoelectric sensor 151 / photoelectric sensing matrix 150 and predicts its next foot position and overall posture specifically includes:

[0144] The processor 300 determines the distance between the feet of the humanoid robot 10 and the wireless charging mat 100 based on the time when the light feedback signal emitted by the photoelectric sensor 151 / photoelectric sensing matrix 150 is received.

[0145] The processor 300 determines the projection position of the humanoid robot 10's feet on the plane of the wireless charging mat 100 based on the feedback signals of light emitted by the photoelectric sensor 151 at different positions in the photoelectric sensor 151 / photoelectric sensing matrix 150.

[0146] Based on the distance between the humanoid robot 10's feet and the wireless charging mat 100, as well as the projection position of the feet on the plane of the wireless charging mat 100, the processor 300 obtains the instantaneous spatial position of the feet. Combined with the humanoid robot 10's own size parameters and walking habits, the processor 300 determines the instantaneous foot position and overall posture of the humanoid robot 10 and predicts its next foot position and overall posture.

[0147] (3) The method by which the processor 300 determines the instantaneous foot position and overall posture of the humanoid robot 10 relative to the wireless charging blanket 100 based on the information acquired by the vision camera 210 and predicts the foot position and overall posture of its next position specifically includes:

[0148] First, the processor 300 determines the instantaneous spatial distance and position between the feet of the humanoid robot 10 and the surface of the wireless charging blanket 100, as well as the overall posture of the humanoid robot 10, based on the three-dimensional image information of the humanoid robot 10's feet, legs, arms, torso, visual beacon 160 and working environment captured by the vision camera 210, and the image relationship between the feet and the surface of the wireless charging blanket 100.

[0149] Then, the processor 300 combines the humanoid robot 10's own size, walking gait and walking habits parameters to predict its next foot position and overall posture.

[0150] (4) The specific method by which the processor 300 determines the instantaneous foot position and overall posture of the humanoid robot 10 relative to the wireless charging blanket 100 and predicts its next foot position and overall posture based on the information acquired by the pressure sensor 141 / pressure sensing matrix 140, the photoelectric sensor 151 / photoelectric sensing matrix 150 and the vision camera 210 includes:

[0151] First, information obtained from pressure sensor 141 / pressure sensing matrix 140 is used to determine the position of the humanoid robot 10's feet and its overall posture, and a trust score is given. Information obtained from photoelectric sensor 151 / photoelectric sensing matrix 150 is used to determine the distance between the humanoid robot 10's feet and the surface of the wireless charging mat 100, the projection position of the humanoid robot 10's feet on the surface of the wireless charging mat 100, and the overall posture of the humanoid robot 10, and a trust score is given. Information obtained from vision camera 210 is used to determine the overall posture of the humanoid robot 10 and the spatial position of its feet, and a trust score is given. Wherein:

[0152] The determination results of the foot position of the humanoid robot 10 by the pressure sensor 141 / pressure sensing matrix 140 are assigned to the reliability level based on the trust score, while the determination results of the overall posture of the humanoid robot 10 are assigned to the credibility level based on the trust score.

[0153] The determination results of the distance between the feet of the humanoid robot 10 and the surface of the wireless charging mat 100 by the photoelectric sensor 151 / photoelectric sensing matrix 150 are rated as reliable based on the trust level. The determination results of the projection position of the feet of the humanoid robot 10 on the surface of the wireless charging mat 100 are rated as reliable based on the trust level. The determination results of the overall posture of the humanoid robot 10 are rated as trustworthy based on the trust level.

[0154] The judgment results of the visual camera 210 on the overall posture of the humanoid robot 10 are determined as reliable level according to the trust score, and the judgment results of the spatial position of the feet of the humanoid robot 10 are determined as sub-reliable level according to the trust score.

[0155] Then, based on the aforementioned trust level rating, the reliability level information is used as the determination result, and the sub-reliability level and trustworthy level information are used as auxiliary references to give the evaluation results of the humanoid robot 10's instantaneous foot position and overall posture, and the prediction results of its foot position and overall posture at the next moment.

[0156] (5) The specific method by which the processor 300 of the artificial intelligence learning processing system determines the instantaneous foot position and overall posture of the humanoid robot 10 relative to the wireless charging blanket 100 and predicts its next foot position and overall posture based on the information obtained by the pressure sensor 141 / pressure sensing matrix 140, the photoelectric sensor 151 / photoelectric sensing matrix 150 and the vision camera 210 includes:

[0157] First, the processor 300, which activates the artificial intelligence learning and processing system, establishes and continuously improves its intelligent positioning model for determining and predicting the instantaneous and next-moment position and posture of the humanoid robot 10 and its radio electromagnetic beam receiver-converter 220 relative to the wireless charging blanket 100 by processing and learning the information acquired by the pressure sensor 141 / pressure sensing matrix 140, photoelectric sensor 151 / photoelectric sensing matrix 150 and / or vision camera 210, as well as the humanoid robot 10's own weight, size, walking gait and walking habit parameters, and through autonomous relearning.

[0158] Then, based on the intelligent positioning model, the artificial intelligence learning and processing system formulates in real time the control rules for the processor 300 to control the electromagnetic beam emission switch, intensity and direction of at least one radio electromagnetic beam transmitting unit of the humanoid robot 10 and its radio electromagnetic beam receiver converter 220 at the immediate location. At the same time, it plans the preparatory rules for at least one radio electromagnetic beam transmitting unit corresponding to the radio electromagnetic beam receiver converter 220 to prepare for the electromagnetic beam emission switch, intensity and direction control in the next moment.

[0159] Finally, the processor 300, based on the control rules and preparation rules formulated and planned by its artificial intelligence learning and processing system, and combined with the real-time characteristic information of the rechargeable battery (not shown in the figure) fed back by the radio electromagnetic beam receiver converter 220 and the real-time working information of the radio electromagnetic beam receiver converter 220, regulates the charging operation of the rechargeable battery (not shown in the figure) of the humanoid robot 10 in the current state and prepares for the charging of the rechargeable battery (not shown in the figure) of the humanoid robot 10 in the next state.

[0160] From the above explanation, it can be seen that:

[0161] In the humanoid robot wireless charging system provided in this embodiment, the pressure sensor / pressure sensing matrix, photoelectric sensor / photoelectric sensing matrix, and vision camera can not only individually constitute observation and measurement devices for the real-time position and posture of the humanoid robot on the wireless charging mat, but can also be used in combination to form a more powerful and comprehensive observation and measurement system. Each different observation and measurement device or system can obtain the real-time position and posture information of the humanoid robot on the wireless charging mat using different methods and from different dimensions. This helps the processor to determine and verify the real-time position and posture of the humanoid robot on the wireless charging mat and predict its position and posture at the next moment through different methods, thus providing a foundation for accurate and efficient full-condition dynamic wireless charging of the humanoid robot.

[0162] The processor determines and predicts the position and posture of the humanoid robot on the wireless charging mat based on the information obtained by the pressure sensor / pressure sensing matrix and / or photoelectric sensor / photoelectric sensing matrix and vision camera. This method is simple, fast, and clear, and can obtain reliable results. This ensures that the humanoid robot, whether standing or walking, can be wirelessly charged accurately and efficiently in all working conditions.

[0163] Because the artificial intelligence learning processing system possesses powerful autonomous learning and modeling capabilities, it can learn from historical data related to the humanoid robot's overall posture and foot trajectory changes. This includes learning from detection data from pressure sensors / pressure sensing matrices, photoelectric sensors / photoelectric sensing matrices, and / or image data from vision cameras. Furthermore, it combines this learning with processing and learning of parameters such as the humanoid robot's weight, size, gait, and walking habits, and autonomous relearning. This allows it to establish a system that determines the humanoid robot's instantaneous foot position and overall posture relative to the wireless charging mat, predicts its next foot position and overall posture, and thereby determines the radio electromagnetic current beam. The intelligent positioning model that receives the instantaneous position and attitude of the converter and predicts its next position and attitude can be seen as an intelligent model that combines rule-based and data learning. This model can be used to extract motion data related to humanoid robots. Since the tasks performed by humanoid robots are usually fixed, after a period of learning, this model can accurately judge and predict the posture and trajectory of humanoid robots. This is similar to how an intelligent agent can learn the entire set of actions of a humanoid robot and infer subsequent posture and trajectory based on current and previous motion characteristics, thus providing a guarantee for intelligent wireless charging of humanoid robots.

[0164] Example 2

[0165] This embodiment provides a method for dynamic wireless charging of a humanoid robot in standing or walking conditions based on any of the humanoid robot wireless charging systems in Embodiment 1 above.

[0166] In this embodiment, the humanoid robot is a humanoid robot powered by a rechargeable battery, and the humanoid robot has a charging interface for charging its rechargeable battery.

[0167] As shown in Figure 1, a wireless charging method for a humanoid robot includes the following steps:

[0168] In the area where the humanoid robot 10 stands or walks, a wireless charging mat 100 of any of the above-mentioned humanoid robot wireless charging systems is laid out, and the visual camera 210 and the radio electromagnetic beam receiver converter 220 of the humanoid robot wireless charging system are placed on the humanoid robot 10. The charging plug of the radio electromagnetic beam receiver converter 220 is connected to the charging interface of the humanoid robot 10. Alternatively, multiple pressure sensors 141 that are distributed in a point-like manner around or above each radio electromagnetic beam transmitting coil 130 are grouped into a pressure sensing matrix 140, and multiple photoelectric sensors 151 that are distributed in a point-like manner on the base mat 110 are grouped into at least one photoelectric sensing matrix 150.

[0169] When the humanoid robot 10 steps onto the wireless charging mat 100, the processor 300 in the humanoid robot wireless charging system determines the instantaneous foot position and overall posture of the humanoid robot 10 relative to the wireless charging mat 100 based on the information obtained by the pressure sensor 141 / pressure sensing matrix 140, the photoelectric sensor 151 / photoelectric sensing matrix 150 and / or the vision camera 210, and predicts its next foot position and overall posture.

[0170] Based on the determined instantaneous foot position and overall posture of the humanoid robot 10 relative to the wireless charging blanket 100, and the predicted foot position and overall posture of the humanoid robot 10 at the next moment, the processor 300 controls at least one radio electromagnetic beam transmitting unit to perform electromagnetic beam transmission switching, intensity and direction control through the following methods: nearby directional transmission, pre-start directional transmission, intelligent transmission through artificial intelligence learning processing system and / or loss-prevention power transmission. This allows at least one radio electromagnetic beam transmitting unit corresponding to the radio electromagnetic beam receiver converter 220 at the next moment to prepare for electromagnetic beam transmission switching, intensity and direction control, thereby enabling the radio electromagnetic beam receiver converter 220 mounted on the humanoid robot 10 to transmit an electromagnetic beam with controlled intensity and direction.

[0171] A wireless electromagnetic beam receiver-converter 220 mounted on the humanoid robot 10 receives an electromagnetic beam and converts it into current to charge a rechargeable battery (not shown in the figure). Simultaneously, the wireless electromagnetic beam receiver-converter 220 sends its real-time operating information and the real-time characteristic information of the rechargeable battery (not shown in the figure) to the processor 300 via a wireless charging local area network. The processor 300 then adjusts and controls the electromagnetic beam transmission switch, intensity, and direction of the wireless electromagnetic beam transmitter unit, thereby enabling dynamic wireless charging of the humanoid robot 10 in its standing or walking state. The real-time operating information of the wireless electromagnetic beam receiver-converter 220 includes its current and voltage information, and the real-time characteristic information of the rechargeable battery (not shown in the figure) includes the battery's charge level.

[0172] From the above description, it can be seen that:

[0173] This embodiment fully utilizes the humanoid robot wireless charging system provided in Embodiment 1. The processor processes the information acquired by the pressure sensor / pressure sensing matrix and / or photoelectric sensor / photoelectric sensing matrix, and the vision camera to determine the humanoid robot's instantaneous position and posture on the wireless charging mat and predict its next position and posture. It then controls at least one wireless electromagnetic beam transmitting unit through methods such as proximity-based directional transmission, pre-activated directional transmission, intelligent transmission control by an artificial intelligence learning processing system, and / or loss-prevention power transmission. Alternatively, it may combine these methods as needed to switch the electromagnetic beam transmission on and off and enhance its intensity. The method involves adjusting the intensity and direction of the electromagnetic beam, and preparing at least one radio electromagnetic beam transmitting unit corresponding to the radio electromagnetic beam receiver-converter to transmit the electromagnetic beam and adjust its intensity and direction. This enables the radio electromagnetic beam receiver-converter mounted on the humanoid robot to transmit an electromagnetic beam with controlled intensity, achieving dynamic wireless charging of the humanoid robot under all working conditions, whether standing or walking. The method is diverse and flexible, safe and convenient to operate, and highly efficient and fast. It is a brand-new technical solution for charging humanoid robots under dynamic conditions under all working conditions, and it has achieved technical effects that existing technologies cannot achieve. Therefore, it has outstanding substantive characteristics and significant progress, and is of great value for promotion and application.

[0174] To better understand the above-mentioned charging method, which describes how at least one radio electromagnetic beam transmitting unit uses methods such as proximity-activated directional transmission, pre-activated directional transmission, intelligent control of transmission by an artificial intelligence learning and processing system, or loss-prevention power transmission to control the electromagnetic beam transmission switch, intensity, and direction, further detailed explanations will be provided below.

[0175] ① The specific method by which the processor 300 controls at least one radio electromagnetic beam transmitting unit to control the switching, intensity, and direction of the electromagnetic beam transmission through a directional transmission method initiated from the nearest location is as follows:

[0176] The processor 300 determines the position of the radio electromagnetic beam receiver-converter 220 based on the real-time foot position and overall posture of the humanoid robot 10, as well as the real-time operating information fed back by the electromagnetic beam receiver-converter and the real-time characteristic information of the rechargeable battery (not shown in the figure). It then controls one radio electromagnetic beam transmitting unit or a radio electromagnetic beam transmitting array composed of multiple radio electromagnetic beam transmitting units on the wireless charging blanket 100 to transmit electromagnetic beams to the radio electromagnetic beam receiver-converter 220, including controlling the transmission switch, intensity, and direction of the electromagnetic beam, while keeping the remaining radio electromagnetic beam transmitting units or radio electromagnetic beam transmitting array in a standby state with their operations suspended.

[0177] ② The specific method by which the processor 300 controls at least one radio electromagnetic beam transmitting unit to adjust the transmission switch, intensity, and direction of the electromagnetic beam through pre-activated directional transmission is as follows:

[0178] The processor 300 determines the position of the radio electromagnetic beam receiver-converter 220 based on the predicted foot position and overall posture of the humanoid robot 10, as well as the real-time operating information fed back by the radio electromagnetic beam receiver-converter 220 and the real-time characteristic information of the rechargeable battery (not shown in the figure). It pre-activates and controls a radio electromagnetic beam transmitting unit or a phased array radio electromagnetic beam transmitting array composed of multiple radio electromagnetic beam transmitting units near the radio electromagnetic beam receiver-converter 220 to transmit electromagnetic beams to the radio electromagnetic beam receiver-converter 220 that has just entered its electromagnetic beam transmission range. It also controls the transmission switch, intensity and direction of the electromagnetic beams, and continuously adjusts the transmission direction and intensity of the electromagnetic beams based on the trajectory of the radio electromagnetic beam receiver-converter 220 and the real-time operating information of the radio electromagnetic beam receiver-converter 220, while keeping the remaining radio electromagnetic beam transmitting units or radio electromagnetic beam transmitting arrays in a standby state with their operations suspended.

[0179] ③ The specific method by which the processor 300 controls at least one radio electromagnetic beam transmitting unit to intelligently control the electromagnetic beam transmission switch, intensity, and direction through an artificial intelligence learning and processing system is as follows:

[0180] Enable the built-in artificial intelligence learning and processing system in the processor 300, making the processor 300 an intelligent processor 300 under the intelligent control of the artificial intelligence learning and processing system;

[0181] The intelligent processor 300, through its artificial intelligence learning and processing system's autonomous learning, correction, and relearning functions, processes and learns the information acquired by the humanoid robot 10 walking on the wireless charging mat 100 from the pressure sensor 141 / pressure sensing matrix 140, photoelectric sensor 151 / photoelectric sensing matrix 150, and / or vision camera 210, and combines the processing and learning of the humanoid robot 10's own weight, size, walking gait, and walking habit parameters, to establish and continuously improve its intelligent positioning model for determining the humanoid robot 10's instantaneous foot position and overall posture relative to the wireless charging mat 100, predicting its next foot position and overall posture, and thereby determining the instantaneous position and posture of the radio electromagnetic beam receiver converter 220 and predicting its next position and posture.

[0182] After the intelligent positioning model learns the working actions of the humanoid robot 10, it accurately predicts the instantaneous foot position and overall posture of the humanoid robot 10 relative to the wireless charging blanket 100 at the next moment for repetitive tasks, identifies the motion data features from the sensors, and then infers the action at the next moment.

[0183] When the humanoid robot 10 steps onto the wireless charging mat 100, the intelligent processor 300 processes the relevant information acquired by the pressure sensor 141 / pressure sensing matrix 140, photoelectric sensor 151 / photoelectric sensing matrix 150 and / or vision camera 210, and combines the humanoid robot 10's own weight, size, walking gait and walking habit parameters, and determines the instantaneous position and attitude of the radio electromagnetic beam receiver converter 220 based on its intelligent positioning model and predicts its position and attitude at the next moment. Based on this, it formulates control rules for the electromagnetic beam emission switch, intensity and direction adjustment of at least one radio electromagnetic beam transmitting unit near the instantaneous position of the humanoid robot 10's radio electromagnetic beam receiver converter 220, and plans preparatory rules for the at least one radio electromagnetic beam transmitting unit corresponding to the radio electromagnetic beam receiver converter 220 at the next moment to prepare for electromagnetic beam emission, intensity and direction adjustment.

[0184] Based on the control rules and preparation rules, as well as the real-time working information fed back by the radio electromagnetic beam receiver-converter 220 and the real-time characteristic information of the rechargeable battery (not shown in the figure), the intelligent processor 300 controls the electromagnetic beam emission switch, intensity, and direction of at least one radio electromagnetic beam emitting unit or radio electromagnetic beam emitting array near the real-time location of the radio electromagnetic beam receiver-converter 220 of the humanoid robot 10. It also prepares at least one radio electromagnetic beam emitting unit corresponding to the radio electromagnetic beam receiver-converter 220 to prepare for the emission and intensity control of the electromagnetic beam in the next moment, thereby realizing the intelligent charging control of the rechargeable battery (not shown in the figure) of the humanoid robot 10.

[0185] ④ The specific method by which the processor 300 controls at least one radio electromagnetic beam transmitting unit to adjust the electromagnetic beam transmission switch, intensity, and direction via loss-prevention variable power transmission is as follows:

[0186] When the processor 300 cannot accurately predict the movement trajectory of the humanoid robot 10's feet, the radio electromagnetic beam receiver-converter 220 receives energy at a power level below its rated power.

[0187] When the feet of the humanoid robot 10 are far from the surface of the wireless charging mat 100, the processor 300 controls the wireless charging transmitter or the wireless magnetocurrent transmitter array to send electromagnetic currents, so that the receiving power of the wireless magnetocurrent receiver converter 220 is slightly lower than its rated value, in order to avoid the wireless charging transmitter or the wireless magnetocurrent transmitter array not adjusting in time due to the increased density of the electromagnetic current when the feet move downwards quickly, which could cause overload damage to the wireless magnetocurrent receiver converter 220.

[0188] When the processor 300 detects that the humanoid robot 10's feet are approaching the wireless charging blanket 100 from a distance, the processor 300 controls the wireless charging transmitter unit or the radio electromagnetic beam transmitter array to gradually adjust the transmission power of the electromagnetic beam from a distance to a distance, so that the energy power received by the radio electromagnetic beam receiver converter 220 gradually approaches its rated value from a small to a large value.

[0189] When the processor 300 detects that the humanoid robot 10's feet are close to the surface area of ​​the wireless charging mat 100, the processor 300 controls the wireless charging transmitter unit or the wireless magnetocurrent transmitter array to send an electromagnetic current, so that the wireless magnetocurrent receiver converter 220 can receive the full load of energy for wireless charging.

[0190] When the processor 300 can accurately and stably predict the movement trajectory of the humanoid robot 10's feet, the processor 300, based on the predicted movement trajectory of the radio electromagnetic beam receiver-converter 220 determined by the humanoid robot 10's next foot position and overall posture, as well as the real-time operating information fed back by the radio electromagnetic beam receiver-converter 220 and the real-time characteristic information of the rechargeable battery (not shown in the figure), pre-activates and regulates a radio electromagnetic beam transmitting unit or a radio electromagnetic beam transmitting array composed of multiple radio electromagnetic beam transmitting units near the next position of the corresponding radio electromagnetic beam receiver-converter 220, preparing for the electromagnetic beam's transmission switch, intensity, and direction control, wherein:

[0191] When the radio magnetocurrent receiver-converter 220 mounted on the humanoid robot 10 approaches the radio magnetocurrent transmitter unit or radio magnetocurrent transmitter array from a distance, the processor 300 adjusts the transmission pattern of the radio magnetocurrent transmitter unit or radio magnetocurrent transmitter array in a timely manner according to the predicted movement trajectory of the radio magnetocurrent receiver-converter 220, so as to ensure that the receiving power of the radio magnetocurrent receiver-converter 220 is always near the rated power.

[0192] When the radio magnetocurrent receiver-converter 220 mounted on the humanoid robot 10 moves away from the radio magnetocurrent transmitter unit or the radio magnetocurrent transmitter array from near to far, the processor 300 adjusts the transmission pattern of the radio magnetocurrent transmitter unit or the radio magnetocurrent transmitter array in a timely manner according to its predicted movement trajectory of the radio magnetocurrent receiver-converter 220, so as to ensure that the receiving power of the radio magnetocurrent receiver-converter 220 is always near the rated power.

[0193] It should be noted that:

[0194] The various specific methods described above for the processor to control at least one radio electromagnetic beam transmitting unit to switch, control the intensity and direction of electromagnetic beam transmission can be selected and / or combined according to actual needs to meet the different charging needs of humanoid robots. Those skilled in the art can make arrangements based on the above methods. However, the selection and / or combination made according to the embodiments given in this specification obviously fall within the protection scope claimed by this application.

[0195] Typically, humanoid robots repeat a certain task, while the intelligent positioning model provided by the artificial intelligence learning and processing system has the ability to learn autonomously. By learning autonomously from the historical motion data of the humanoid robot and extracting the motion data features as needed, it can further improve the accuracy of the intelligent positioning model in positioning and prediction.

[0196] The intelligent positioning model learns about the humanoid robot's overall posture and foot trajectory data, including not only the information acquired by the pressure sensor / pressure sensing matrix and / or photoelectric sensor / photoelectric sensing matrix and vision camera, but also the above data and the humanoid robot's past position judgment and posture prediction rules. It then extracts the relevant motion feature data of the humanoid robot to continuously update and improve its intelligent positioning model.

[0197] As can be seen, the specific method for using any of the humanoid robot wireless charging systems in Embodiment 1 to perform dynamic wireless charging of humanoid robots in standing or walking conditions can be different depending on the requirements and needs, thereby achieving efficient, fast and safe wireless charging of humanoid robots powered by rechargeable batteries in their standing or walking working conditions, which is flexible, convenient and safe.

[0198] In conclusion, it can be seen that:

[0199] This invention constructs a novel wireless charging system for humanoid robots by integrating a wireless charging blanket, ferrite, radio electromagnetic beam transmitting coil, pressure sensor, photoelectric sensor, and visual beacon, along with a visual camera, radio electromagnetic beam receiver-converter, wireless communication server, and processor with a built-in artificial intelligence learning processing system. The wireless charging blanket has a compact structure and reasonable layout, making it easy to use and move. When laid in the standing or moving work area of ​​the humanoid robot, it does not affect the original working mode of the humanoid robot, but can provide it with dynamic and efficient wireless charging services under all working conditions, thereby improving the endurance and working efficiency of the humanoid robot and allowing it to exert greater utility.

[0200] The observation and measurement system constructed by the present invention, using pressure sensors, photoelectric sensors and vision cameras, either individually or in combination, can quickly, timely and accurately capture the real-time position and posture of a humanoid robot on a wireless charging mat. This provides a reliable basis for the processor to determine and predict the real-time and next-time position and posture of the radio magnetocurrent receiver converter, thereby ensuring efficient and accurate charging.

[0201] The wireless charging local area network, which consists of a vision camera, a wireless magnetocurrent transmitting coil, a wireless magnetocurrent receiving converter, and a wireless communication server, and is connected to the processor and includes pressure sensors and photoelectric sensors, ensures the rapid and timely transmission and processing of the humanoid robot's real-time posture and position information on the wireless charging mat, as well as the real-time power information of the humanoid robot's rechargeable battery. This enables the humanoid robot wireless charging system provided by this invention to perform efficient, accurate, and dynamic charging of the humanoid robot's rechargeable battery.

[0202] The application of an artificial intelligence learning and processing system further enables the humanoid robot wireless charging system provided by this invention to implement efficient and precise charging control in an intelligent manner.

[0203] Furthermore, the charging method provided by this invention is flexible and convenient, and different methods can be adopted according to charging requirements and needs, so that humanoid robots can complete wireless charging efficiently, quickly and safely in standing or walking working conditions.

[0204] In summary, the humanoid robot wireless charging system and charging method provided by this invention overcome the shortcomings of the prior art, enabling dynamic and efficient wireless charging services for humanoid robots in standing or moving operations under all working conditions, improving their endurance and work efficiency, allowing them to exert greater utility, achieving technical effects that the prior art cannot achieve, possessing outstanding substantive features and significant progress, and having great promotion and application value.

[0205] In the description process of the above instruction manual:

[0206] The terms “this embodiment,” “an embodiment of the present invention,” “as shown,” “further,” etc., are used to indicate that the specific features, structures, materials, or characteristics described in the embodiment are included in at least one embodiment of the present invention. In this specification, the illustrative expressions of the above terms are not necessarily directed at the same embodiment, and the specific features, structures, materials, or characteristics described may be combined or combined in a suitable manner in any one or more embodiments.

[0207] Furthermore, without creating contradictions, those skilled in the art can combine or integrate the different embodiments described in this specification and the features of the different embodiments.

[0208] Finally, it should be noted that:

[0209] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions described in the embodiments of the present invention. Non-essential improvements, adjustments or substitutions made by those skilled in the art based on the contents described in this specification are all within the scope of protection claimed by the present invention.

Claims

1. A humanoid robot wireless charging system for wireless charging of a power source for a charging battery of a humanoid robot in a standing or walking work condition of the humanoid robot, wherein, The human-shaped robot has a charging interface for charging its battery, and is characterized in that it comprises a base mat, a ferrite, a wireless electromagnetic beam emitting coil, a pressure sensor, a photoelectric sensor, a visual beacon, a visual camera, a wireless electromagnetic beam receiving converter, a wireless communication server and a processor with an artificial intelligence learning processing system, wherein the base mat, the ferrite, the wireless electromagnetic beam emitting coil, the pressure sensor, the photoelectric sensor and the visual beacon constitute an integrated wireless charging mat, the base mat is used to lay on the area where the human-shaped robot stands or travels, the ferrite is laid on the base mat, a plurality of wireless electromagnetic beam emitting coils are embedded in the base mat respectively, each wireless electromagnetic beam emitting coil further constitutes a wireless electromagnetic beam emitting unit with its corresponding ferrite, a plurality of pressure sensors are arranged around or above the wireless electromagnetic beam emitting coils respectively, a plurality of photoelectric sensors and a plurality of visual beacons with different labels or shapes are arranged on the base mat respectively, the visual beacons with different labels or shapes are used to mark different areas of the wireless charging mat and different environments; the visual camera and the wireless electromagnetic beam receiving converter are arranged on the human-shaped robot respectively, the visual camera is a binocular wide-angle wearable stereo camera with a built-in rotating mechanism that can automatically adjust the shooting direction, the wireless electromagnetic beam receiving converter is provided with a charging plug that can cooperate with the charging interface of the human-shaped robot, the visual camera, the wireless electromagnetic beam receiving converter and the wireless charging mat are further respectively provided with a communication function module and together constitute a wireless charging local area network with the wireless communication server, the wireless charging local area network is in communication with the processor and is regulated by the processor, the pressure sensor and the photoelectric sensor are also in information communication with the processor; when the human-shaped robot walks into the wireless charging mat, the pressure sensor, the photoelectric sensor and the visual camera acquire the real-time pressure information, the photoelectric sensing information, the position and posture and the surrounding environment image information of the human-shaped robot on the wireless charging mat respectively, and the above information and the characteristic information of the battery of the human-shaped robot are also sent to the processor through the wireless charging local area network, the processor or the processor with the artificial intelligence learning processing system regulates the electromagnetic beam emitting switch, intensity and direction of at least one wireless electromagnetic beam emitting unit of the wireless electromagnetic beam receiving converter closest to the human-shaped robot after processing these information, the wireless electromagnetic beam receiving converter on the human-shaped robot converts the electromagnetic beam emitted by the wireless electromagnetic beam emitting unit into electric current to charge the battery of the human-shaped robot.A plurality of pressure sensors are arranged around or above each of the wireless electromagnetic flux beam emitting coils and are distributed in a dot-like manner to form a pressure sensor matrix corresponding to each of the wireless electromagnetic flux beam emitting coils, which is used to obtain the pressure and pressure distribution information generated by the soles of the humanoid robot on the wireless charging mat and send them to the processor; a plurality of photoelectric sensors are arranged on the base mat and are distributed in a dot-like manner to form one or more photoelectric sensing matrices on the base mat, which is used to obtain the spatial position information of the soles of the humanoid robot on the wireless charging mat, including the height difference between the soles and the wireless charging mat and the projection position information of the soles on the wireless charging mat and send them to the processor; the visual camera is worn on the head, neck or torso of the humanoid robot, which is used to obtain the image information of the soles, legs, arms, torso, visual beacon and working environment of the humanoid robot and send them to the processor; the processor or the processor with an artificial intelligence learning processing system determines the instantaneous sole position and overall posture of the humanoid robot relative to the wireless charging mat according to the information obtained by the pressure sensor / pressure sensor matrix, the photoelectric sensor / photoelectric sensing matrix and / or the visual camera, and predicts its next moment sole position and overall posture, thereby determining the instantaneous and next moment position and posture of the wireless electromagnetic flux beam receiver, thereby controlling the emission of electromagnetic flux beam of at least one of the wireless electromagnetic flux beam emitting units closest to the instantaneous position of the wireless electromagnetic flux beam receiver of the humanoid robot, and preparing the emission of electromagnetic flux beam of at least one of the wireless electromagnetic flux beam emitting units corresponding to the next moment wireless electromagnetic flux beam receiver.

2. The humanoid robot wireless charging system of claim 1, wherein: The base mat is made of high-molecular flexible flame-retardant material, the ferrite is a flexible ferrite sheet, the wireless electromagnetic flux beam receiving converter is a wearable shoe / boots-shaped wireless electromagnetic flux beam receiving converter, and the shoe / boots-shaped wireless electromagnetic flux beam receiving converter is worn / sleeved on the soles of the humanoid robot; the shoe / boots-shaped wireless electromagnetic flux beam receiving converter comprises a flexible high-molecular sole base, a flexible ferrite sheet fixed in the sole base, an electromagnetic flux beam receiving coil, a wireless communication device and a microcontroller, wherein the flexible ferrite sheet and the electromagnetic flux beam receiving coil together form a wireless electromagnetic flux beam receiving unit, the wireless communication device is used for wireless communication of the shoe / boots-shaped wireless electromagnetic flux beam receiving converter, and the microcontroller is used for overall work regulation and control of the shoe / boots-shaped wireless electromagnetic flux beam receiving converter.

3. The humanoid robot wireless charging system of claim 1, wherein: The method for determining the instant sole position and overall posture of the humanoid robot relative to the wireless charging mat and predicting the next moment sole position and overall posture of the humanoid robot according to the information obtained by the pressure sensor / pressure sensor matrix comprises the following steps: when the pressure sensor / pressure sensor matrix measures the pressure of both soles of the humanoid robot and the pressure distribution information is consistent, the processor determines that the humanoid robot is in a standing state at this moment, and then determines the instant sole position and overall posture of the humanoid robot and predicts the next moment sole position and overall posture of the humanoid robot according to the position of the pressure sensor detecting the pressure, the weight of the humanoid robot, the stride distance, the work requirement and the walking habit; when the pressure sensor / pressure sensor matrix only detects the pressure of a single sole of the humanoid robot or the momentary pressure of both soles of the humanoid robot and the pressure distribution information thereof, the processor first determines that the humanoid robot is walking, then determines the position of the sole of the humanoid robot according to the position of the pressure sensor detecting the pressure, and determines the walking direction of the humanoid robot according to the pressure distribution information of the sole, and then determines the instant overall posture of the humanoid robot and predicts the next moment sole position and overall posture of the humanoid robot based on the weight of the humanoid robot, the stride distance, the walking habit, the determined sole position and the walking direction; when the pressure sensor / pressure sensor matrix detects the momentary pressure of both soles of the humanoid robot and the pressure distribution information of each sole, the processor first determines the raised foot and the supporting foot of the humanoid robot at this moment, i.e. the sole in the area with continuously increasing pressure is the supporting foot of the humanoid robot, and the sole in the area with continuously decreasing pressure is the raised foot of the humanoid robot; then, the processor determines the overall posture of the humanoid robot and predicts the next moment sole position and overall posture of the humanoid robot based on the weight of the humanoid robot, the stride distance and the walking habit.

4. The humanoid robot wireless charging system of claim 1, wherein: The method for determining the real-time foot position and overall posture of the humanoid robot relative to the wireless charging blanket and predicting the foot position and overall posture of the humanoid robot at the next moment by the processor according to the information obtained by the photoelectric sensor / photoelectric sensing matrix comprises: the processor determines the distance between the foot of the humanoid robot and the wireless charging blanket according to the time when the light feedback signal emitted by the photoelectric sensor / photoelectric sensing matrix is received; the processor determines the projection position of the foot of the humanoid robot on the plane of the wireless charging blanket according to the light feedback signal emitted by the photoelectric sensor / photoelectric sensing matrix at different positions; the processor determines the real-time spatial position of the foot based on the distance between the foot of the humanoid robot and the wireless charging blanket and the projection position on the plane of the wireless charging blanket, and then determines the real-time foot position and overall posture of the humanoid robot and predicts the foot position and overall posture of the humanoid robot at the next moment by combining the size parameters and walking habits of the humanoid robot.

5. The humanoid robot wireless charging system of claim 1, wherein: The method for determining the real-time foot position and overall posture of the humanoid robot relative to the wireless charging blanket and predicting the foot position and overall posture of the humanoid robot at the next moment by the processor according to the information obtained by the visual camera comprises: first, the processor determines the real-time spatial distance and position between the foot of the humanoid robot and the surface of the wireless charging blanket and the overall posture of the humanoid robot according to the three-dimensional image information of the foot, leg, arm, torso, visual beacon and working environment of the humanoid robot and the image relationship between the foot and the surface of the wireless charging blanket captured by the visual camera; then, the processor predicts the foot position and overall posture of the humanoid robot at the next moment by combining the size, walking gait and walking habit parameters of the humanoid robot.

6. The humanoid robot wireless charging system of claim 1, wherein: The processor determines the real-time foot position and overall posture of the humanoid robot relative to the wireless charging mat and predicts its foot position and overall posture at the next moment according to the information obtained by the pressure sensor / pressure sensor matrix, the photoelectric sensor / photoelectric sensor matrix and the visual camera. The specific method includes: first, determining the foot position of the humanoid robot and the overall posture of the humanoid robot according to the information obtained by the pressure sensor / pressure sensor matrix and giving a trust score; determining the distance between the foot of the humanoid robot and the surface of the wireless charging mat, the projection position of the foot of the humanoid robot on the surface of the wireless charging mat and the overall posture of the humanoid robot according to the information obtained by the photoelectric sensor / photoelectric sensor matrix and giving a trust score; determining the overall posture of the humanoid robot and the spatial position of the foot of the humanoid robot according to the information obtained by the visual camera and giving a trust score. Wherein: the determination result of the foot position of the humanoid robot by the pressure sensor / pressure sensor matrix is determined as a reliable level according to the trust score, and the determination result of the overall posture of the humanoid robot is determined as a trusted level according to the trust score; the determination result of the distance between the foot of the humanoid robot and the surface of the wireless charging mat by the photoelectric sensor / photoelectric sensor matrix is determined as a reliable level according to the trust score, the determination result of the projection position of the foot of the humanoid robot on the surface of the wireless charging mat is determined as a reliable level according to the trust score, and the determination result of the overall posture of the humanoid robot is determined as a trusted level according to the trust score; the determination result of the overall posture of the humanoid robot by the visual camera is determined as a reliable level according to the trust score, and the determination result of the spatial position of the foot of the humanoid robot is determined as a less reliable level according to the trust score; then, according to the above trust score levels, the reliable level information is taken as the determination result, and the less reliable level and trusted level information are taken as auxiliary references to give the evaluation result of the real-time foot position and overall posture of the humanoid robot and the prediction result of its foot position and overall posture at the next moment.

7. The humanoid robot wireless charging system of claim 1, wherein: The processor of the artificial intelligence learning processing system determines the real-time foot position and overall posture of the humanoid robot relative to the wireless charging blanket and predicts the next moment foot position and overall posture according to the information obtained by the pressure sensor / pressure sensor matrix, the photoelectric sensor / photoelectric sensor matrix and the vision camera. The specific method includes: first, the processor of the artificial intelligence learning processing system processes and learns the information obtained by the pressure sensor / pressure sensor matrix, the photoelectric sensor / photoelectric sensor matrix and / or the vision camera, as well as the weight, size, walking gait and walking habit parameters of the humanoid robot itself, and continuously improves the intelligent positioning model for determining and predicting the real-time and next moment position and posture of the humanoid robot and its wireless electromagnetic flow beam receiver relative to the wireless charging blanket through autonomous relearning; then, the artificial intelligence learning processing system formulates the control rules of the processor for the electromagnetic flow beam emission switch, intensity and direction regulation of at least one wireless electromagnetic flow beam emission unit close to the real-time position of the humanoid robot and its wireless electromagnetic flow beam receiver according to the intelligent positioning model in real time, and plans the preparation rules for the electromagnetic flow beam emission switch, intensity and direction regulation of at least one wireless electromagnetic flow beam emission unit corresponding to the wireless electromagnetic flow beam receiver in the next moment; finally, the processor regulates and controls the charging operation of the humanoid robot and its charging battery in the real-time state according to the control rules and preparation rules formulated and planned by the artificial intelligence learning processing system, and makes the charging preparation of the humanoid robot and its charging battery in the next state, combined with the real-time characteristic information of the charging battery and the real-time working information of the wireless electromagnetic flow beam receiver fed back by the wireless electromagnetic flow beam receiver.

8. A humanoid robot wireless charging method for dynamic wireless charging of a humanoid robot having a charging battery as a power source and a charging interface in a standing or walking working condition of the humanoid robot, characterized in that, The method comprises the following steps: laying the wireless charging mat in the humanoid robot wireless charging system according to any one of claims 1-7 in the area where the humanoid robot stands or walks, and arranging the visual camera and the wireless electromagnetic flux beam receiving converter in the humanoid robot wireless charging system on the humanoid robot, connecting the charging plug of the wireless electromagnetic flux beam receiving converter with the charging interface of the humanoid robot, or further grouping the plurality of pressure sensors distributed in a dot-like form around or above each wireless electromagnetic flux beam emitting coil into a pressure sensor matrix, and grouping the plurality of photoelectric sensors distributed in a dot-like form on the base mat into at least one photoelectric sensing matrix; when the humanoid robot walks onto the wireless charging mat, the processor in the humanoid robot wireless charging system determines the real-time foot position and overall posture of the humanoid robot relative to the wireless charging mat and predicts the foot position and overall posture of the humanoid robot at the next moment according to the information obtained by the pressure sensors / pressure sensor matrix, the photoelectric sensors / photoelectric sensing matrix, and / or the visual camera; according to the determined real-time foot position and overall posture of the humanoid robot relative to the wireless charging mat and the predicted foot position and overall posture of the humanoid robot at the next moment, the processor controls at least one wireless electromagnetic flux beam emitting unit to perform electromagnetic flux beam emission switch, intensity, and direction control through near-field directional emission, pre-directional emission, artificial intelligence learning system intelligent emission, and / or lossless power emission mode, and prepares at least one wireless electromagnetic flux beam emitting unit corresponding to the wireless electromagnetic flux beam receiving converter at the next moment for electromagnetic flux beam emission switch, intensity, and direction control, so as to emit electromagnetic flux beam with controlled intensity and direction for the wireless electromagnetic flux beam receiving converter arranged on the humanoid robot; the wireless electromagnetic flux beam receiving converter arranged on the humanoid robot receives the electromagnetic flux beam and converts it into electric current to charge the charging battery, at the same time, the wireless electromagnetic flux beam receiving converter sends its real-time working information and the real-time characteristic information of the charging battery to the processor through the wireless charging local area network, and the processor adjusts and controls the electromagnetic flux beam emission switch, intensity, and direction of the wireless electromagnetic flux beam emitting unit, so as to realize dynamic wireless charging of the humanoid robot in the standing or walking working condition, wherein the real-time working information of the wireless electromagnetic flux beam receiving converter includes its current and voltage information, and the real-time characteristic information of the charging battery includes the power information of the charging battery. 9.The humanoid robot wireless charging method of claim 8, wherein: The specific method for the processor to control the emission switch, intensity and direction of the electromagnetic flux beam of at least one wireless electromagnetic flux beam emission unit through the on-the-spot starting directional emission mode is as follows: the processor controls one wireless electromagnetic flux beam emission unit or a wireless electromagnetic flux beam emission array composed of multiple wireless electromagnetic flux beam emission units on the wireless charging blanket to implement the emission of electromagnetic flux beam to the wireless electromagnetic flux beam receiving converter according to the position of the wireless electromagnetic flux beam receiving converter determined by the real-time foot position and overall posture of the humanoid robot and the real-time working information of the wireless electromagnetic flux beam receiving converter and the real-time characteristic information of the charging battery, including the control of the emission switch, intensity and direction of the electromagnetic flux beam, while the remaining wireless electromagnetic flux beam emission units or the wireless electromagnetic flux beam emission array are in the standby state of suspended work. 10.The humanoid robot wireless charging method of claim 9, wherein: The specific method for the processor to control the emission switch, intensity and direction of the electromagnetic flux beam of at least one wireless electromagnetic flux beam emission unit through the pre-starting directional emission mode is as follows: the processor pre-starts and controls one wireless electromagnetic flux beam emission unit or a phased array wireless electromagnetic flux beam emission array composed of multiple wireless electromagnetic flux beam emission units at a position near the wireless electromagnetic flux beam receiving converter according to the position of the wireless electromagnetic flux beam receiving converter determined by the predicted next moment foot position and overall posture of the humanoid robot and the real-time working information of the wireless electromagnetic flux beam receiving converter and the real-time characteristic information of the charging battery, implements the emission of electromagnetic flux beam to the wireless electromagnetic flux beam receiving converter which has just entered the electromagnetic flux beam emission range thereof, controls the emission switch, intensity and direction of the electromagnetic flux beam, and constantly adjusts the emission direction and intensity of the electromagnetic flux beam according to the travel trajectory of the wireless electromagnetic flux beam receiving converter and the real-time working information of the wireless electromagnetic flux beam receiving converter, while the remaining wireless electromagnetic flux beam emission units or the wireless electromagnetic flux beam emission array are in the standby state of suspended work. 11.The humanoid robot wireless charging method of claim 9, wherein: The processor regulates the at least one wireless electromagnetic current beam emitting unit to emit electromagnetic current beam through the intelligent emission mode of the artificial intelligence learning processing system. The specific method for regulating the opening, intensity and direction of the electromagnetic current beam emission is as follows: the built-in artificial intelligence learning processing system in the processor is turned on, and the processor is in an intelligent processing mode under the intelligent control of the artificial intelligence learning processing system; the intelligent processor establishes and continuously improves an intelligent positioning model for determining the real-time sole position and overall posture of the humanoid robot relative to the wireless charging blanket and predicting the next moment sole position and overall posture of the humanoid robot, and determining the real-time position and posture of the wireless electromagnetic current beam receiver and predicting the next moment position and posture of the wireless electromagnetic current beam receiver, through the autonomous learning and autonomous correction and relearning functions of the artificial intelligence learning processing system, through the processing and learning of the information acquired by the pressure sensor / pressure sensing matrix, the photoelectric sensor / photoelectric sensing matrix and / or the visual camera, and in combination with the processing and learning of the weight, size, walking gait and walking habit parameters of the humanoid robot; after the intelligent positioning model learns the work action of the humanoid robot, the real-time sole position and overall posture of the humanoid robot relative to the wireless charging blanket at the next moment are accurately predicted, the motion data characteristics from the sensor are identified, and the next moment action is inferred; after the humanoid robot walks onto the wireless charging blanket, the intelligent processor determines the real-time position and posture of the wireless electromagnetic current beam receiver and predicts the next moment position and posture of the wireless electromagnetic current beam receiver according to the intelligent positioning model, in combination with the weight, size, walking gait and walking habit parameters of the humanoid robot, and formulates control rules for regulating the opening, intensity and direction of the electromagnetic current beam emission of the at least one wireless electromagnetic current beam emitting unit closest to the real-time position of the wireless electromagnetic current beam receiver of the humanoid robot, and plans preparatory rules for the at least one wireless electromagnetic current beam emitting unit corresponding to the wireless electromagnetic current beam receiver at the next moment to prepare for the opening, intensity and direction regulation of the electromagnetic current beam emission, through the processing of the relevant information acquired by the pressure sensor / pressure sensing matrix, the photoelectric sensor / photoelectric sensing matrix and / or the visual camera; the intelligent processor regulates the opening, intensity and direction of the electromagnetic current beam emission of the at least one wireless electromagnetic current beam emitting unit or the wireless electromagnetic current beam emitting array closest to the real-time position of the wireless electromagnetic current beam receiver of the humanoid robot, and prepares for the opening, intensity and direction regulation of the electromagnetic current beam emission of the at least one wireless electromagnetic current beam emitting unit corresponding to the wireless electromagnetic current beam receiver at the next moment, so as to realize intelligent charging control of the charging battery of the humanoid robot. ​ 12.The humanoid robot wireless charging method of claim 9, wherein: The specific method for the processor to regulate the on-off, intensity and direction of the electromagnetic beam emission of the at least one wireless electromagnetic beam emission unit through the anti-damage power emission mode is as follows: when the processor cannot accurately predict the movement trajectory of the sole of the humanoid robot, the wireless electromagnetic beam receiver converts energy in a mode lower than the rated power, that is, when the position of the sole of the humanoid robot is far away from the wireless charging carpet, the processor controls the wireless charging emission unit or the wireless electromagnetic beam emission array to send electromagnetic beams, so that the wireless electromagnetic beam receiver receives power slightly lower than the rated value, to avoid the overloading and damage of the wireless electromagnetic beam receiver due to the rapid downward movement of the sole and the increase of the density of the electromagnetic beam, which causes the wireless charging emission unit or the wireless electromagnetic beam emission array to fail to adjust in time; when the processor detects that the position of the sole of the humanoid robot is approaching the wireless charging carpet, the processor controls the wireless charging emission unit or the wireless electromagnetic beam emission array to gradually regulate the sending power of the electromagnetic beam from far to near, so that the wireless electromagnetic beam receiver gradually receives power close to the rated value from small to large. When the processor detects that the foot sole position of the humanoid robot is close to the surface area of the wireless charging blanket, the processor controls the wireless charging transmitting unit or the wireless electromagnetic beam transmitting array to send electromagnetic beams, so that the wireless electromagnetic beam receiving converter can receive full-load energy for wireless charging; when the processor can accurately and stably predict the motion trajectory of the foot sole of the humanoid robot, the processor determines the motion trajectory of the wireless electromagnetic beam receiving converter according to the predicted next moment foot sole position and overall posture of the humanoid robot, the real-time working information fed back by the wireless electromagnetic beam receiving converter, and the real-time characteristic information of the charging battery, and pre-starts and regulates one wireless electromagnetic beam transmitting unit or a wireless electromagnetic beam transmitting array composed of multiple wireless electromagnetic beam transmitting units corresponding to the next moment position of the wireless electromagnetic beam receiving converter, and prepares for the emission switch, intensity and direction regulation of electromagnetic beams, wherein: when the wireless electromagnetic beam receiving converter arranged on the humanoid robot approaches the wireless electromagnetic beam transmitting unit or the wireless electromagnetic beam transmitting array from far to near, the processor adjusts the emission rule of the wireless electromagnetic beam transmitting unit or the wireless electromagnetic beam transmitting array in time according to the predicted motion trajectory of the wireless electromagnetic beam receiving converter, to ensure that the receiving power of the wireless electromagnetic beam receiving converter is always near the rated power; when the wireless electromagnetic beam receiving converter arranged on the humanoid robot moves away from the wireless electromagnetic beam transmitting unit or the wireless electromagnetic beam transmitting array from near to far, the processor adjusts the emission rule of the wireless electromagnetic beam transmitting unit or the wireless electromagnetic beam transmitting array in time according to the predicted motion trajectory of the wireless electromagnetic beam receiving converter, to ensure that the receiving power of the wireless electromagnetic beam receiving converter is always near the rated power.

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