Control method of intelligent device, intelligent device and computer readable storage medium

Abstract

The invention relates to the technical field of intelligent control, in particular to a control method of intelligent equipment, the intelligent equipment and a computer readable storage medium, and aims to solve the technical problem of how to realize stable following and effective obstacle avoidance of the intelligent equipment. In order to achieve the purpose, a UWB-AOA base station and a laser radar are arranged on the intelligent device, the total horizontal coverage angle of the UWB-AOA base station is an omnidirectional angle in the horizontal direction, and positioning information of a UWB tag is obtained based on the UWB-AOA base station; acquiring environment obstacle information based on the laser radar; path planning is carried out according to the positioning information and the environmental obstacle information, and a path planning result is obtained; and according to the path planning result, the intelligent device is controlled, so that the intelligent device can follow the UWB tag, omnidirectional tracking of the UWB tag can be realized, and the obstacle avoidance range and precision of the intelligent device are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent control, in particular to a control method of intelligent equipment, intelligent equipment and a computer readable storage medium. BACKGROUND

[0002] At present, there are various intelligent equipment for industrial material handling in the market, such as automatic following equipment, intelligent following vehicle, etc. Such equipment often performs environment perception based on vision, infrared and other sensors to achieve path planning and autonomous following.

[0003] However, the intelligent equipment for industrial material handling in the prior art uses a vision sensor to collect data, which may cause the tracking target to be lost or misidentified. For example, in a production workshop, employees often wear uniforms, so that the target tracking based on vision is easy to be confused, resulting in loss or misidentification of the following target. At the same time, due to the limitation of the detection angle, the existing intelligent equipment has a problem of angle detection blind area, which leads to path deviation, tracking failure and other problems of the following equipment. In addition, the traditional ultrasonic and infrared sensors have the inherent defect of narrow field of view angle, which leads to the problems of insufficient coverage range of the automatic following equipment, and thus cannot effectively avoid obstacles.

[0004] Correspondingly, there is a need in the art for a new control scheme of intelligent equipment to solve the above problems. SUMMARY

[0005] In order to overcome the above-mentioned defects, the present application is proposed to solve or at least partially solve the technical problem of how to realize stable following and effective obstacle avoidance of intelligent equipment.

[0006] In a first aspect, a control method of intelligent equipment is provided, which is applied to intelligent equipment, wherein a UWB-AOA base station and a laser radar are arranged on the intelligent equipment; the total horizontal coverage angle of the UWB-AOA base station is the omnidirectional angle in the horizontal direction; and the method comprises:

[0007] obtaining positioning information of the UWB tag based on the UWB-AOA base station;

[0008] obtaining environment obstacle information based on the laser radar;

[0009] performing path planning according to the positioning information and the environment obstacle information to obtain a path planning result;

[0010] controlling the intelligent equipment according to the path planning result to realize following of the intelligent equipment to the UWB tag.

[0011] In a technical solution of the control method of the intelligent device, the path planning is performed according to the positioning information and the environmental obstacle information, and a path planning result is obtained, including:

[0012] According to the positioning information and the environmental obstacle information, data fusion is performed to obtain a data fusion result.

[0013] According to the data fusion result, path planning is performed to obtain the path planning result.

[0014] In a technical solution of the control method of the intelligent device, the path planning is performed according to the data fusion result to obtain the path planning result, including:

[0015] According to the data fusion result, path planning is performed based on an optimized dynamic window method to obtain the path planning result.

[0016] In a technical solution of the control method of the intelligent device, the data fusion is performed according to the positioning information and the environmental obstacle information to obtain a data fusion result, including:

[0017] According to the positioning information and the environmental obstacle information, data fusion is performed based on an extended Kalman filter algorithm to obtain a data fusion result.

[0018] In a technical solution of the control method of the intelligent device, the control of the intelligent device is performed according to the path planning result, including:

[0019] According to the path planning result and the environmental obstacle information, the intelligent device is controlled.

[0020] In a technical solution of the control method of the intelligent device, the control of the intelligent device is performed according to the path planning result and the environmental obstacle information, including:

[0021] According to the path planning result and the environmental obstacle information, a distance between an obstacle in a path corresponding to the path planning result and the intelligent device is obtained.

[0022] If the distance is less than or equal to a first preset distance, the intelligent device is controlled to perform obstacle avoidance processing on the obstacle.

[0023] If the distance is greater than the first preset distance, the intelligent device is controlled according to the distance and the path planning result.

[0024] In a technical solution of the control method of the intelligent device, the control of the intelligent device to perform obstacle avoidance processing on the obstacle includes:

[0025] If the distance is greater than a second preset distance, controlling the intelligent device to perform emergency braking;

[0026] If the distance is less than or equal to the second preset distance, controlling the intelligent device to retreat a third preset distance;

[0027] The second preset distance is less than the first preset distance.

[0028] In one of the technical solutions of the control method of the intelligent device, the controlling the intelligent device according to the distance and the path planning result comprises:

[0029] If the distance is greater than or equal to a fourth preset distance, controlling the intelligent device to follow the UWB tag according to the path planning result;

[0030] If the distance is less than the fourth preset distance, controlling the intelligent device to slow down and adjust the path planning result, and controlling the intelligent device according to the adjusted path planning result;

[0031] The fourth preset distance is greater than the first preset distance.

[0032] In one of the technical solutions of the control method of the intelligent device, the obtaining the positioning information of the UWB tag based on the UWB-AOA base station comprises:

[0033] Receiving, by the UWB-AOA base station, a UWB signal sent by the UWB tag;

[0034] Obtaining, according to the UWB signal, a relative distance and a relative angle of the UWB tag relative to the intelligent device as the positioning information.

[0035] In one of the technical solutions of the control method of the intelligent device, the laser radar is a 360-degree laser radar.

[0036] In a second aspect, an intelligent device is provided, which comprises a UWB-AOA base station, a laser radar, at least one processor, and a memory in communication connection with the at least one processor, wherein the memory stores a computer program which, when executed by the at least one processor, implements the method of any one of the technical solutions of the control method of the intelligent device.

[0037] In a third aspect, a computer-readable storage medium is provided, wherein a plurality of program codes are stored in the computer-readable storage medium, the program codes being adapted to be loaded and run by a processor to execute the method of any one of the technical solutions of the control method of the intelligent device.

[0038] Scheme 1. A control method of an intelligent device, characterized in that the method is applied to an intelligent device, wherein a UWB-AOA base station and a laser radar are arranged on the intelligent device; a total horizontal coverage angle of the UWB-AOA base station is an omnidirectional angle in a horizontal direction; and the method comprises:

[0039] Based on the UWB-AOA base station, positioning information of the UWB tag is acquired;

[0040] Based on the laser radar, environmental obstacle information is acquired;

[0041] According to the positioning information and the environmental obstacle information, path planning is performed to acquire a path planning result;

[0042] According to the path planning result, the intelligent device is controlled to realize following of the UWB tag by the intelligent device.

[0043] Scheme 2. The control method of the intelligent device according to scheme 1, characterized in that,

[0044] The path planning according to the positioning information and the environmental obstacle information to acquire the path planning result comprises:

[0045] According to the positioning information and the environmental obstacle information, data fusion is performed to acquire a data fusion result;

[0046] According to the data fusion result, path planning is performed to acquire the path planning result.

[0047] Scheme 3. The control method of the intelligent device according to scheme 2, characterized in that,

[0048] The path planning according to the data fusion result to acquire the path planning result comprises:

[0049] According to the data fusion result, path planning is performed based on an optimized dynamic window method to acquire the path planning result.

[0050] Scheme 4. The control method of the intelligent device according to scheme 2, characterized in that,

[0051] The data fusion according to the positioning information and the environmental obstacle information to acquire the data fusion result comprises:

[0052] Based on an extended Kalman filtering algorithm, data fusion is performed according to the positioning information and the environmental obstacle information, and a data fusion result is obtained.

[0053] Scheme 5. The control method of the intelligent device according to scheme 1, characterized in that,

[0054] The control of the intelligent device according to the path planning result comprises:

[0055] The control of the intelligent device according to the path planning result and the environmental obstacle information.

[0056] Scheme 6. The control method of the intelligent device according to scheme 5, characterized in that,

[0057] The control of the intelligent device according to the path planning result and the environmental obstacle information comprises:

[0058] According to the path planning result and the environmental obstacle information, a distance between an obstacle in a path corresponding to the path planning result and the intelligent device is obtained.

[0059] If the distance is less than or equal to a first preset distance, the intelligent device is controlled to perform obstacle avoidance processing on the obstacle.

[0060] If the distance is greater than the first preset distance, the intelligent device is controlled according to the distance and the path planning result.

[0061] Scheme 7. The control method of the intelligent device according to scheme 6, characterized in that,

[0062] The control of the intelligent device to perform obstacle avoidance processing on the obstacle comprises:

[0063] If the distance is greater than a second preset distance, the intelligent device is controlled to perform emergency braking.

[0064] If the distance is less than or equal to the second preset distance, the intelligent device is controlled to retreat by a third preset distance.

[0065] The second preset distance is less than the first preset distance.

[0066] Scheme 8. The control method of the intelligent device according to scheme 6, characterized in that,

[0067] The control of the intelligent device according to the distance and the path planning result comprises:

[0068] If the distance is greater than or equal to a fourth preset distance, the smart device is controlled to follow the UWB tag according to the path planning result.

[0069] If the distance is less than the fourth preset distance, the smart device is controlled to slow down and adjust the path planning result, and the smart device is controlled according to the adjusted path planning result.

[0070] The fourth preset distance is greater than the first preset distance.

[0071] Scheme 9. The control method of the smart device according to scheme 1, characterized in that,

[0072] The positioning information of the UWB tag is obtained based on the UWB-AOA base station, and the positioning information includes:

[0073] The UWB-AOA base station receives the UWB signal sent by the UWB tag.

[0074] The relative distance and the relative angle of the UWB tag relative to the smart device are obtained according to the UWB signal as the positioning information.

[0075] Scheme 10. The control method of the smart device according to scheme 1, characterized in that,

[0076] The laser radar is a 360-degree laser radar.

[0077] Scheme 11. A smart device, characterized in that, comprising:

[0078] A UWB-AOA base station; the total horizontal coverage angle of the UWB-AOA base station is the omnidirectional angle in the horizontal direction.

[0079] A laser radar;

[0080] At least one processor;

[0081] And a memory in communication connection with the at least one processor;

[0082] The memory stores a computer program, and the computer program is executed by the at least one processor to realize the control method of the smart device according to any one of schemes 1 to 10.

[0083] Scheme 12. A computer readable storage medium, wherein a plurality of program codes are stored, characterized in that the program codes are suitable for being loaded and run by a processor to execute the control method of the smart device according to any one of schemes 1 to 10.

[0084] The one or more technical solutions of the application have at least one or more of the following beneficial effects.

[0085] In the implementation of the control method of the intelligent device provided by the application, the UWB-AOA base station and the laser radar are arranged on the intelligent device, the total horizontal coverage angle of the UWB-AOA base station is the omnidirectional angle in the horizontal direction, the positioning information of the UWB tag is obtained based on the UWB-AOA base station, the environmental obstacle information is obtained based on the laser radar, the path planning is performed according to the positioning information and the environmental obstacle information, the path planning result is obtained, and the intelligent device is controlled according to the path planning result to realize the following of the UWB tag by the intelligent device. Through the above configuration mode, the omnidirectional tracking of the UWB tag can be realized according to the omnidirectional UWB-AOA base station, the problem of angle detection blind area is avoided, and it is ensured that the accurate positioning information of the UWB tag can be obtained at any position within the tracking radius of the intelligent device. Combined with the laser radar for obstacle monitoring, the obstacle avoidance range and accuracy of the intelligent device can be effectively improved. The combination of the positioning information and the environmental obstacle for path planning, and the following of the UWB tag according to the path planning result, can effectively avoid the problems of UWB tag loss and misidentification, realize the stable following of the UWB tag by the intelligent device, and improve the practicability and safety of the intelligent device.

[0086] Further, the laser radar of the application is a 360-degree laser radar, which can realize omnidirectional obstacle monitoring and further effectively improve the obstacle avoidance coverage range and accuracy.

[0087] Further, the combination of the positioning information obtained by the UWB-AOA base station and the environmental obstacle information obtained by the laser radar can realize stable data fusion, ensure a high-reliability data fusion process in a complex data environment, and further improve the reliability of path planning.

[0088] Further, the combination of the path planning result and the environmental obstacle information realizes the control of the intelligent device, ensures the emergency braking and obstacle avoidance processing such as backward movement of the intelligent device in the case of small distance from the obstacle, and further effectively improves the safety and practicability of the intelligent device application in the scene of frequent personnel flow and obstacle interference. BRIEF DESCRIPTION OF DRAWINGS

[0089] The disclosure of the application will become more apparent with reference to the accompanying drawings. It is easily understood by those skilled in the art that the drawings are only for illustrative purposes, and are not intended to limit the scope of protection of the application. Among them:

[0090] Figure 1 is a main step flow diagram of the control method of the intelligent device according to an embodiment of the application;

[0091] Figure 2 FIG. 1 is a schematic diagram of a main system structure of a smart device according to an embodiment of the present application;

[0092] Figure 3 FIG. 2 is a schematic diagram of main steps of a control method of a smart device according to an embodiment of the present application;

[0093] Figure 4 FIG. 3 is a schematic diagram of a detour test track of a smart device according to an example of the present application. DETAILED DESCRIPTION

[0094] Some embodiments of the present application will be described below with reference to the accompanying drawings. It should be understood by those skilled in the art that the embodiments are only used to explain the technical principles of the present application, and are not intended to limit the protection scope of the present application.

[0095] In the description of the present application, "module", "processor" can include hardware, software or a combination of both. A module can include hardware circuit, various suitable sensors, communication port, memory, and can also include software part such as program code, and can be a combination of software and hardware. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The term "at least one of A or B" or "at least one of A and B" has a similar meaning as "A and / or B", and can include only A, only B, or A and B. The singular form of the term "one", "this" can also include the plural form.

[0096] The relevant user personal information that can be involved in the embodiments of the present application is strictly in accordance with the requirements of laws and regulations, and follows the principles of legality, legitimacy and necessity, and is based on the reasonable purpose of business scene, and processes the personal information of the user which is actively provided by the user in the process of using the product / service or generated due to the use of the product / service, and authorized by the user.

[0097] The user personal information processed by the present application will be different due to the specific product / service scene, and the specific scene of the user using the product / service should be used as the standard, which can involve the user's account information, device information, driving information, vehicle information or other related information. The present application will treat the user's personal information and its processing with high diligence.

[0098] The present application attaches great importance to the security of user personal information, and has taken security protection measures in accordance with industry standards, which are reasonable and feasible to protect the user's information, prevent unauthorized access, public disclosure, use, modification, damage or loss of personal information.

[0099] Some terms related to the present application will be explained first.

[0100] UWB(Ultra Wide Band, ultra-wideband) technology is a wireless carrier communication technology that does not use a sinusoidal carrier, but transmits data using nanosecond-level non-sinusoidal wave narrow pulses, so its frequency spectrum range is very wide.

[0101] AOA(Angle-of-Arrival, angle of arrival ranging) is a technology that realizes positioning by sensing the direction of arrival of a signal, and determines the position of a target by using the relative position or angle information between a receiving node and an anchor node, combined with the triangulation method.

[0102] UWB-AOA, single base station positioning technology based on ultra-wideband. That is, a solution for realizing single base station accurate positioning using ultra-wideband technology, which measures the angle of arrival (AOA) of a signal by deploying a phased array antenna at the base station end and combines time of flight (TOF) ranging. For example, positioning accuracy of ±10 centimeters can be achieved within a radius of 50 meters.

[0103] DWA(Dynamic Window Approach, dynamic window approach) is a real-time path planning algorithm that avoids dynamic obstacles by evaluating feasible trajectories within a speed window.

[0104] Extended Kalman Filter (EKF) is an improved Kalman filter method for state estimation of nonlinear systems, which realizes real-time optimal estimation of dynamic systems through local linearization processing.

[0105] Referring to the accompanying Figure 1 , Figure 1 is the main step flowchart of the control method of the intelligent device according to an embodiment of the present application. As shown in Figure 1 , the UWB-AOA base station and the laser radar are arranged on the intelligent device in the embodiment of the present application; the total horizontal coverage angle of the UWB-AOA base station is the omnidirectional angle in the horizontal direction. The control method of the intelligent device in the embodiment of the present application mainly includes the following steps S101 to S104.

[0106] Step S101: Based on the UWB-AOA base station, the positioning information of the UWB tag is obtained.

[0107] In this embodiment, the UWB-AOA base station can cover the omnidirectional angle in the horizontal direction, that is, it can realize 360-degree omnidirectional accurate identification of the UWB tag. The positioning information of the UWB tag can be obtained by tracking the UWB tag through the UWB-AOA base station.

[0108] In one embodiment, step S101 can further include the following steps S1011 and S1012:

[0109] Step S1011: receiving the UWB signal sent by the UWB tag based on the UWB-AOA base station.

[0110] Step S1012: obtaining the relative distance and the relative angle of the UWB tag relative to the intelligent device as the positioning information according to the UWB signal.

[0111] In this embodiment, the UWB-AOA base station can receive the UWB signal sent by the UWB tag, and calculate the relative distance (r) and the relative angle (θ) of the UWB tag relative to the intelligent device according to the received UWB signal.

[0112] In one embodiment, the intelligent device can be a smart following vehicle, an automatic following device, a mobile robot, or the like.

[0113] In one specific example, the UWB-AOA base station can adopt a multi-antenna to form an omnidirectional array, the signal radius thereof can be 100 m, the update frequency thereof can be 10 Hz, the receiving frequency thereof can be 6.5 GHz, and the positioning accuracy thereof can be within ±5 cm / ±3°.

[0114] In one embodiment, in a production workshop scenario, the employees in the workshop can wear UWB tags, and the intelligent device can follow the UWB tags worn by the employees. In this way, the problem that different employees wearing the same work clothes cannot be distinguished when the employees are followed by a camera or the like, resulting in confusion of the followed objects, loss of the target, or misidentification, can be effectively solved. The employees wearing the UWB tags to realize the following of the intelligent device can achieve the uniqueness of target identification, improve the following accuracy, and improve the work efficiency and safety.

[0115] Step S102: obtaining the environmental obstacle information based on the laser radar.

[0116] In this embodiment, the position, distance, contour, and the like of the obstacles in the environment around the intelligent device can be detected in real time based on the laser radar to construct a local obstacle map as the environmental obstacle information, which provides a basis for path planning and obstacle avoidance processing.

[0117] In one embodiment, the laser radar can be a 360-degree laser radar. The 360-degree laser radar can realize omnidirectional obstacle monitoring, effectively improving the obstacle avoidance coverage range and accuracy.

[0118] In one specific example, the laser radar can be a 360-degree single-line laser radar, which adopts a 905 nm wavelength, a scanning radius of 30 meters, an update frequency of 10 Hz, and an accuracy of ±3 cm, and can realize real-time detection of the position, distance, and contour of the surrounding obstacles.

[0119] In another example, the laser radar can be a 270-degree single-line laser radar.

[0120] The single-line laser radar can be a single-line laser radar of a brand such as SICK / HOKUYO.

[0121] Step S103: path planning is performed according to the positioning information and the environmental obstacle information, and a path planning result is obtained.

[0122] In this embodiment, the path planning can be performed in combination with the positioning information and the environmental obstacle information, so as to obtain the path planning result.

[0123] In one embodiment, step S103 can further include the following step S1031 and step S1032:

[0124] Step S1031: data fusion is performed according to the positioning information and the environmental obstacle information, and a data fusion result is obtained.

[0125] In this embodiment, the positioning information and the environmental obstacle information are fused, so as to obtain the data fusion result. The data fusion can be implemented by using a commonly used data fusion algorithm in the field.

[0126] In one specific embodiment, the data fusion algorithm can be an extended Kalman filter (EKF) algorithm. The data fusion of the positioning information and the environmental obstacle information can be implemented based on the EKF algorithm, so as to obtain the data fusion result.

[0127] Step S1032: path planning is performed according to the data fusion result, and a path planning result is obtained.

[0128] In this embodiment, the path planning can be performed based on the data fusion result, so as to obtain the path planning result. The path planning can be implemented by using a commonly used path planning algorithm in the field.

[0129] In one specific embodiment, the path planning algorithm can be an optimized dynamic window approach (DWA). The real-time path planning can be implemented based on the optimized DWA algorithm, so as to obtain the path planning result. The optimized DWA algorithm reduces the window length and uses a window mean value to determine the path planning in the window, under the premise of ensuring the accuracy of the obstacle avoidance, wherein the window mean value can include a distance mean value of a relative distance between the obstacle and the intelligent device and an angle mean value of a relative angle.

[0130] Step S104: the intelligent device is controlled according to the path planning result, so as to realize the following of the UWB tag by the intelligent device.

[0131] In the embodiment, the control of the intelligent device can be implemented based on the path planning result, so as to realize the following of the UWB tag by the intelligent device.

[0132] In one embodiment, the intelligent device can be controlled according to the path planning result and the environmental obstacle information. That is, the following of the UWB tag is realized by combining the path planning result and the environmental obstacle information.

[0133] In one embodiment, step S104 can further include steps S1041 to S1043:

[0134] Step S1041: According to the path planning result and the environmental obstacle information, the distance between the obstacle in the path corresponding to the path planning result and the intelligent device is obtained.

[0135] In the embodiment, the distance between the obstacle in the path corresponding to the path planning result and the intelligent device can be obtained by combining the path planning result and the environmental obstacle information.

[0136] Step S1042: If the distance is less than or equal to the first preset distance, the intelligent device is controlled to avoid the obstacle.

[0137] In the embodiment, the obtained distance can be compared with the first preset distance, and if the distance is less than or equal to the first preset distance, the intelligent device can be controlled to avoid the obstacle.

[0138] Specifically, if the distance is less than or equal to the first preset distance and greater than the second preset distance, the intelligent device is controlled to perform emergency braking; if the distance is less than or equal to the second preset distance, the intelligent device is controlled to retreat by the third preset distance; wherein the second preset distance is less than the first preset distance.

[0139] In one specific example, the first preset distance can be 0.3 meters, the second preset distance can be 0.2 meters, and the third preset distance can be 0.1 meters. When the distance between the front end of the intelligent device and the obstacle is less than 0.3 meters and greater than 0.2 meters, the intelligent device can be controlled to perform emergency braking. When the distance between the front end of the intelligent device and the obstacle is less than 0.2 meters, the intelligent device can be controlled to retreat by 0.1 meters to avoid collision.

[0140] It should be noted that the numerical values in the above examples are only exemplary, and a person skilled in the art can set the values of the first preset distance, the second preset distance and the third preset distance according to the actual application needs.

[0141] Step S1043: If the distance is greater than the first preset distance, the intelligent device is controlled according to the distance and the path planning result.

[0142] In the embodiment, if the distance between the front end of the intelligent device and the obstacle is greater than the first preset distance, the intelligent device can be controlled in combination with the distance between the front end of the intelligent device and the obstacle and the path planning result, so as to realize the following of the UWB tag.

[0143] Specifically, if the distance is greater than or equal to the fourth preset distance, the intelligent device is controlled to follow the UWB tag according to the path planning result; if the distance is less than the fourth preset distance and greater than the first preset distance, the intelligent device is controlled to slow down, and the path planning result is adjusted, and the intelligent device is controlled according to the adjusted path planning result; wherein the fourth preset distance is greater than the first preset distance.

[0144] That is, when the distance between the front end of the intelligent device and the obstacle is greater than or equal to the fourth preset distance, the following of the UWB tag can be maintained according to the path planning result, and the path planning is performed in real time during the following process, and the detour path is calculated.

[0145] When the distance between the front end of the intelligent device and the obstacle is less than the fourth preset distance and greater than the first preset distance, the intelligent device can be controlled to slow down, and the path planning result is adjusted to avoid collision with the obstacle.

[0146] In one specific example, the fourth preset distance can be 1 meter. Those skilled in the art can also set the value of the fourth preset distance according to the actual application needs.

[0147] In one embodiment, the following process of the intelligent device to the UWB tag can be monitored, and when there is an abnormal situation, the intelligent device can be controlled to stop running and issue an alarm prompt. Those skilled in the art can set the abnormal situation according to the actual application needs.

[0148] Based on the method described in steps S101 to S104, the smart device of the embodiment of the application is provided with a UWB-AOA base station and a laser radar. The total horizontal coverage angle of the UWB-AOA base station is the omnidirectional angle in the horizontal direction. Based on the UWB-AOA base station, the positioning information of the UWB tag is obtained. Based on the laser radar, the environmental obstacle information is obtained. According to the positioning information and the environmental obstacle information, path planning is performed to obtain a path planning result. According to the path planning result, the smart device is controlled to realize the following of the UWB tag by the smart device. Through the above configuration mode, the embodiment of the application can realize omnidirectional tracking of the UWB tag based on the omnidirectional UWB-AOA base station, avoid the problem of angle detection blind area, and ensure that the accurate positioning information of the UWB tag can be obtained at any position within the tracking radius range of the smart device. Combined with the laser radar for obstacle monitoring, the obstacle avoidance range and accuracy of the smart device can be effectively improved. Combined with the positioning information and the environmental obstacle for path planning, and according to the path planning result, the following of the UWB tag can be realized, which can effectively avoid the problems of UWB tag loss or misidentification, realize stable following of the UWB tag by the smart device, and improve the practicality and safety of the smart device.

[0149] Further, the laser radar of the embodiment of the application is a 360-degree laser radar, which can realize omnidirectional obstacle monitoring and further effectively improve the obstacle avoidance coverage range and accuracy.

[0150] Further, the embodiment of the application combines the positioning information obtained by the UWB-AOA base station and the environmental obstacle information obtained by the laser radar to realize stable data fusion, ensure a high-reliability data fusion process in a complex data environment, and further effectively improve the reliability of path planning.

[0151] Further, the embodiment of the application combines the path planning result and the environmental obstacle information to realize control of the smart device, ensures emergency braking and obstacle avoidance processing such as backward movement of the smart device in the case of small distance from the obstacle, and further effectively improves the safety and practicality of the smart device application in the scene of frequent personnel flow and obstacle interference.

[0152] The following takes the smart device as an example of a smart following vehicle, and the control method of the smart device is further described. Figures 2 to 4 The control method of the smart device of the embodiment of the application is further described.

[0153] As shown in Figure 2 , the smart device can include an actuator device, a power system, a following vehicle controller, and an external control and interaction module.

[0154] The following trolley controller includes a central controller MCU (Microcontroller Unit), a one-line laser radar (i.e., single-line laser radar), and a USB-AOA base station. The one-line laser radar receives obstacle information of obstacles through optical signals and sends it to the central controller MCU through TTL (Transistor-Transistor Logic). The UWB-AOA base station receives radio signals (i.e., UWB signals) of a positioning bracelet (i.e., a UWB tag) and sends them to the central controller MCU through an RS232 interface.

[0155] The central controller MCU can include an STM series high-performance microcontroller (such as an STM32F7 series with built-in floating-point operation reaction), integrate sensor data fusion algorithms, and realize real-time processing and decision output of multi-source data.

[0156] The central controller MCU is connected with a motor, an electronic brake system, and a steering mechanism in the actuator device through an Rs485 interface. The motor can be a double-sided hub motor with a power of 300Wx2. The motor, the electronic brake system, and the steering mechanism form a motion execution module, support a maximum load of 100kg, and a maximum running speed of 1.6m / s. The motor supports CAN bus / RS485 communication. The electronic brake system can realize a braking distance less than or equal to 0.5m (at a speed of 1.6m / s). The steering mechanism can realize a minimum turning radius of 0.6m through differential steering.

[0157] The power supply system includes a power battery and a DCDC (Direct Current-Direct Current Converter) unit. The power supply system provides a 24V power supply for the following trolley controller and is grounded (GND). The power supply system uses a large-capacity lithium battery pack, has a continuous running time of 7-8 hours, and a maximum single running distance of 25 kilometers. In addition, the power supply system is also configured with a charging and current monitoring circuit.

[0158] The central controller MCU is also connected with an external control and interaction module. The external control and interaction module can realize optional configuration, and is used for system state display, parameter setting, and manual control of the intelligent device.

[0159] The entire system refreshes data and executes update control commands at a fixed period (such as 30ms) to maintain the effective following of the UWB tag by the intelligent following trolley.

[0160] As shown in Figure 3 The control method of the intelligent device can be realized according to the following steps:

[0161] First, the intelligent following vehicle system is powered on and initialized; a START command is waited for, the motor is enabled; the main loop is started; sensor data collection is performed, including UWB and laser radar. Data fusion processing is performed based on the data collected by the UWB and the laser radar; state judgment is performed according to the data fusion result; if the distance between the obstacle and the intelligent following vehicle is a normal distance (such as greater than a first preset distance), the following state is maintained, and obstacle detection is continuously performed; if there is an obstacle, obstacle avoidance processing is performed; if there is no obstacle, normal following is performed. After the obstacle avoidance processing, it is judged whether path planning is needed; if needed, path planning is performed; if not needed, PID (proportion-integral-derivative) control speed output is performed; in the state judgment, if the distance between the obstacle and the intelligent following vehicle is too close (such as, less than or equal to a second preset distance), the intelligent following vehicle is controlled to retreat, and PID control speed output is performed; if the distance between the obstacle and the intelligent following vehicle is a suitable distance (such as, less than or equal to the first preset distance and greater than the second preset distance), the intelligent following vehicle is controlled to stop, and PID control speed output is performed; after the PID control speed output, the motor output is controlled, and the main loop is returned.

[0162] As shown in Figure 4 , the intelligent following vehicle can be tested according to the test trajectory shown in Figure 4 to realize function verification of the intelligent following vehicle. Among them, the test includes curve test, lateral test, dynamic obstacle avoidance test, normal stop test, retreat test, emergency stop (braking) test, straight following and acceleration test (5m), U-turn test, etc.

[0163] By using the control method of the embodiment of the present application, the intelligent following vehicle can obtain the following technical effects:

[0164] (1) Positioning accuracy is improved: the UWB-AOA technology provides angle information, so that the following path deviation is controlled within ±5cm / ±3°, and the accuracy is improved by more than 30% compared with the traditional scheme;

[0165] (2) Obstacle avoidance response is fast: the laser radar 10Hz update frequency cooperates with the fusion algorithm to realize 30ms level obstacle avoidance response, and the response speed is improved by 3 times compared with the prior art;

[0166] (3) Safe and reliable operation: multi-level safety mechanism ensures fast braking and safe retreat in emergency, and the accident rate is reduced by 85%;

[0167] (4) Strong environmental adaptability: suitable for complex industrial environments, and can handle dynamic scenes with multiple personnel and multiple obstacles;

[0168] (5) Significant practicality: effectively replaces manual push car operation, saves non-value-added time by more than 20%, and improves work efficiency.

[0169] It should be noted that although the above embodiments describe the steps in a specific order, those skilled in the art can understand that, in order to achieve the effects of the present application, the different steps do not have to be executed in such an order, and they can be executed simultaneously (in parallel) or in other orders. The solutions after these adjustments belong to equivalent technical solutions, and thus will also fall within the protection scope of the present application.

[0170] Those skilled in the art can understand that all or part of the processes in the method of the above embodiment can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of the above various method embodiments can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable storage medium can include any entity or device, medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal and software distribution medium, etc. that can carry the computer program code.

[0171] Another aspect of the present application also provides a computer readable storage medium.

[0172] In an embodiment of the computer readable storage medium according to the present application, the computer readable storage medium can be configured to store a program of the control method of the intelligent device executing the above method embodiments, which can be loaded and run by the processor to implement the above control method of the intelligent device. For ease of illustration, only the parts related to the embodiments of the present application are shown, and the specific technical details not disclosed are referred to the method part of the embodiments of the present application. The computer readable storage medium can be a storage device formed by various electronic devices, such as a magnetic disk, a hard disk, an optical disk, a flash memory, a read-only memory, a random access memory, etc. Optionally, the computer readable storage medium in the embodiments of the present application is a non-transitory computer readable storage medium.

[0173] Another aspect of the present application also provides an intelligent device.

[0174] In an embodiment of the smart device according to the present application, the smart device can comprise a UWB-AOA base station, a laser radar, at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program, and the computer program is executed by the at least one processor to implement the method according to any one of the above embodiments. The total horizontal coverage angle of the UWB-AOA base station is the horizontal omnidirectional angle. The smart device according to the present application can comprise a driving device, a smart vehicle, a robot, a smart following vehicle, etc.

[0175] In some embodiments of the present application, the smart device can further comprise at least one sensor for sensing information. The sensor is communicatively connected to any one of the processors mentioned in the present application. Optionally, the smart device can further comprise an automatic driving system for guiding the smart device to drive by itself or to assist driving. The processor is communicatively connected to the sensor and / or the automatic driving system to implement the method according to any one of the above embodiments. The processor can be a central processor, a microprocessor, an image processor, a digital signal processor or any other suitable processor. The processor has data and / or signal processing functions. The processor can be implemented in software, hardware or a combination of both.

[0176] So far, the technical solution of the present application has been described in combination with one embodiment shown in the drawings, but it is easy for those skilled in the art to understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to the related technical features without departing from the principles of the present application, and the technical solutions after the changes or replacements will fall within the protection scope of the present application.

Claims

1. A control method for an intelligent device, characterized in that, The method is applied to a smart device, and a UWB-AOA base station and a laser radar are arranged on the smart device; a total horizontal coverage angle of the UWB-AOA base station is an omnidirectional angle in a horizontal direction; and the method comprises the following steps: Based on the UWB-AOA base station, positioning information of the UWB tag is acquired; Based on the laser radar, environmental obstacle information is acquired; According to the positioning information and the environmental obstacle information, path planning is performed to acquire a path planning result; According to the path planning result, the smart device is controlled to realize following of the UWB tag by the smart device.

2. The control method of the smart device according to claim 1, wherein the path planning is performed according to the positioning information and the environmental obstacle information to acquire the path planning result, comprising: According to the positioning information and the environmental obstacle information, data fusion is performed to acquire a data fusion result; According to the data fusion result, path planning is performed to acquire the path planning result.

3. The control method of the smart device according to claim 2, wherein the path planning is performed according to the data fusion result to acquire the path planning result, comprising: Based on an optimized dynamic window method, the path planning is performed according to the data fusion result to acquire the path planning result.

4. The control method of the smart device according to claim 2, wherein the data fusion is performed according to the positioning information and the environmental obstacle information to acquire the data fusion result, comprising: Based on an extended Kalman filter algorithm, the data fusion is performed according to the positioning information and the environmental obstacle information to acquire the data fusion result.

5. The control method of the smart device according to claim 1, wherein the smart device is controlled according to the path planning result, comprising: According to the path planning result and the environmental obstacle information, the smart device is controlled.

6. The control method of the smart device according to claim 5, wherein the smart device is controlled according to the path planning result and the environmental obstacle information, comprising: According to the path planning result and the environmental obstacle information, a distance between an obstacle in a path corresponding to the path planning result and the smart device is acquired; If the distance is less than or equal to a first preset distance, the smart device is controlled to perform obstacle avoidance processing on the obstacle; If the distance is greater than the first preset distance, the smart device is controlled according to the distance and the path planning result.

7. The control method of the smart device according to claim 6, wherein the smart device is controlled to perform obstacle avoidance processing on the obstacle, comprising: If the distance is greater than a second preset distance, the smart device is controlled to perform emergency braking; If the distance is less than or equal to the second preset distance, the smart device is controlled to retreat by a third preset distance; Wherein, the second preset distance is less than the first preset distance. ​ ​ ​ ​ ​ ​ 8.The control method of claim 6, wherein the controlling the intelligent device according to the distance and the path planning result comprises: if the distance is greater than or equal to a fourth preset distance, controlling the intelligent device to follow the UWB tag according to the path planning result; and if the distance is less than the fourth preset distance, controlling the intelligent device to decelerate and adjusting the path planning result, and controlling the intelligent device according to the adjusted path planning result; wherein the fourth preset distance is greater than the first preset distance. 9.The control method of claim 1, wherein the obtaining the positioning information of the UWB tag based on the UWB-AOA base station comprises: receiving, by the UWB-AOA base station, a UWB signal sent by the UWB tag; and obtaining, according to the UWB signal, a relative distance and a relative angle of the UWB tag relative to the intelligent device as the positioning information. 10.The control method of claim 1, wherein the laser radar is a 360-degree laser radar. ​ ​ ​ ​ ​ ​ ​ ​

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