Multi-sensing channel based cleaning robot charging method, robot and system

Abstract

The application discloses a multi-perception channel-based cleaning robot charging method, a robot and a system, which are used for controlling a cleaning robot body to move to a base station for charging, planning a charging path according to a first priority charging position, and analyzing an image around the body in real time during driving along the charging path; when a two-dimensional code of a target base station is found, a current body position is calculated according to data obtained by a vehicle-mounted laser radar; if the current body position is not in a preset visible area of the target base station stored, a base station posture of the target base station relative to the body is calculated according to current position characteristics of the two two-dimensional codes analyzed, and an actual coordinate position of the target base station is calculated; the actual coordinate position is updated as the first priority charging position, a matched pre-stopping position is calculated, the body is driven to approach the pre-stopping position, and a relay in the body is started to perform a charging operation after connection between body connecting contacts and base station connecting contacts is completed. The adaptability of the cleaning robot to a complex environment is improved, and the precision and stability of charging positioning are improved.

Description

Technical Field

[0001] This invention relates to the field of robot control technology, and in particular to a charging method, robot, and system for a cleaning robot based on multiple sensing channels. Background Technology

[0002] With the rapid expansion of the smart home ecosystem, intelligent cleaning robots have become a core category of home service robots, widely used in homes, offices, and other scenarios. Currently, autonomous charging technology, as a core auxiliary function of cleaning robots, has gradually upgraded from basic contact charging to intelligent positioning charging. Existing charging methods for cleaning robots often involve the charging dock emitting infrared signals or radio beacons. After receiving the corresponding signals, the robot plans its return path based on its own sensor data and then moves to the charging dock to complete charging; or it uses LiDAR to build an environmental map and navigates back to the charging dock based on preset charging dock location information. However, existing technologies still suffer from weak anti-interference capabilities, and changes in ambient light can easily cause signal recognition failure; single LiDAR positioning solutions are sensitive to the environment, have large positioning errors, and cannot accurately obtain the charging dock location, leading to charging failure or docking deviation, thus affecting charging efficiency and failing to achieve efficient and stable autonomous charging. Summary of the Invention

[0003] This invention addresses the shortcomings of existing technologies by providing a charging method for a cleaning robot based on multi-sensor channels. The method controls the cleaning robot to move to a base station for charging. The base station is equipped with two QR codes identifying the base station's information. The method includes the following steps: Step S1: Based on the charging command, plan the charging path according to the pre-stored first priority charging position, and analyze the images around the machine collected by the front-end camera in real time while driving along the charging path; when the QR code of the target base station is found in the image around the machine, calculate the current position of the machine based on the data obtained by the vehicle-mounted LiDAR.

[0004] Step S2: If the current location of the device is not within the preset visible area of ​​the stored target base station, the base station attitude of the target base station relative to the device is calculated based on the current location features of the two parsed QR codes, and the actual coordinate position of the target base station is calculated based on the base station attitude and the current location of the device.

[0005] Step S3: Update the actual coordinate position to the first priority charging position, and calculate the matching pre-stop position based on the updated first priority charging position; drive the machine body to approach the pre-stop position, and after the machine body connecting contact and the base station connecting contact are connected, activate the relay in the machine body to perform charging operation.

[0006] Preferably, the body connection contact includes a body communication interface and a body power interface; the base station includes a housing and a base station connection contact installed on the front of the housing, the base station connection contact including a base station communication interface and a base station power interface that match the body connection contact; two QR codes are configured on the base station housing on the same side as the base station connection contact and are arranged horizontally at intervals, wherein the two QR codes respectively contain base station fixed encoding information and base station type encoding information; a light source that can provide illumination for the QR codes is installed on one side or the back of the QR codes; and two horizontally arranged strong reflective strips arranged at intervals are also attached to the base station housing on the same side as the base station connection contact for calibration and positioning.

[0007] Preferably, step S3 includes: real-time detection of the position of the machine body and the target base station; when the distance between the machine body and the target base station is lower than the connection threshold but no connection feedback between the machine body's communication interface and the base station's communication interface is detected, it is determined that the current charging connection has failed and the machine body is controlled to leave the pre-parking position; the machine body is controlled to drive back to the pre-parking position again and the connection status with the base station's communication interface is detected in real time; if no connection with the base station's communication interface is detected, the machine body is driven away again until the communication connection is successful or the number of consecutive connection failures exceeds a preset value, at which point the docking with the current target base station is suspended.

[0008] Preferably, step S3 further includes: adjusting the original first priority charging position to a second priority charging position, updating the actual coordinate position to the first priority charging position; calculating a matching pre-stop position based on the updated first priority charging position; driving the machine body to approach the pre-stop position, and activating the relay inside the machine body to perform charging operation after the machine body connecting contact and the base station connecting contact are connected; if the machine body connecting contact and the base station connecting contact fail to connect multiple times, then planning a second charging path based on the second priority charging position, and controlling the machine body to move along the second charging path to the second priority charging position.

[0009] Preferably, the base station is equipped with an observable level bubble device for presenting the current horizontal state of the base station. Step S3 further includes: after the connection between the body connector and the base station connector fails, acquiring a level bubble image containing the level bubble device, locating the bubble slot using edge detection / circular detection, identifying bubble features using the Hough circle transform algorithm and projecting them onto the main axis of the bubble slot, obtaining base station flatness evaluation data after obtaining the mapping through linear fitting; if the base station has a horizontal offset and the offset exceeds a threshold, then issuing base station offset information; simultaneously acquiring measurement data of inertial devices inside the body, calculating the front and rear tilt state of the vehicle body based on the inertial device measurement data, and issuing body attitude offset information if the body pitch angle exceeds a set threshold.

[0010] Preferably, if a second base station is detected in the image around the vehicle during driving, the base station type is obtained by parsing the QR code information on the second base station. If the base station type is compatible with the current vehicle's charging interface and the current vehicle position is not within the preset visible area of ​​the stored supporting base station, the coordinates of the second base station on the map are calculated based on the two QR codes on the second base station and the current vehicle position, and recorded in the base station information database. When the vehicle reaches the pre-parking position of the supporting base station but the supporting base station is not detected, the second base station is replaced with the current vehicle's supporting base station, and a new charging path is re-planned and generated based on the coordinates of the second base station. After the vehicle reaches the second base station and completes the communication connection, the identity information of the second base station is obtained, and the identity information of the second base station is added to the vehicle's supporting base station information.

[0011] This invention also discloses a charging device for a cleaning robot based on multi-sensor channels, comprising: a position estimation module, which plans a charging path according to a pre-stored first priority charging position based on a charging command, and analyzes images of the robot's surroundings captured by a front-end camera in real time while traveling along the charging path; when a QR code of a target base station is detected in the images of the robot's surroundings, the current position of the robot is estimated based on data obtained by an onboard LiDAR; a position calculation module, which, if the current position of the robot is not within a preset visible area of ​​the stored target base station, calculates the base station attitude of the target base station relative to the robot based on the current position features of the two QR codes analyzed, and calculates the actual coordinate position of the target base station based on the base station attitude and the current position of the robot; a connection charging module, which updates the actual coordinate position to the first priority charging position, and calculates a matching pre-parking position based on the updated first priority charging position; drives the robot to approach the pre-parking position, and activates a relay inside the robot to perform charging operation after the robot's connecting contact and the base station connecting contact are connected.

[0012] Preferably, the charging module is further configured to: detect the position of the host and the target base station in real time; when the distance between the host and the target base station is lower than the connection threshold but no connection feedback between the host's communication interface and the base station's communication interface is detected, determine that the current charging connection has failed and control the host to leave the pre-parking position; control the host to drive back to the pre-parking position again and detect the connection status with the base station's communication interface in real time; if no connection with the base station's communication interface is detected, drive away again until the communication connection is successful or the number of connection failures exceeds a preset value, then suspend the docking with the current target base station.

[0013] The present invention also discloses a robot, including a body on which a processor and a memory are mounted, the memory being used to store a computer program executable by the processor, wherein the processor is configured to execute the computer program in the memory to implement the steps of the multi-sensory channel-based cleaning robot charging method as described above.

[0014] The present invention also discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the charging method for a cleaning robot based on multiple sensing channels as described above.

[0015] This invention discloses a charging method, robot, and system for a cleaning robot based on multi-sensor channels. The robot is used to control its movement to a base station for charging. The base station has two QR codes identifying its location. A charging path is planned according to a pre-stored first priority charging position based on a charging command. During the robot's movement along the charging path, images of the robot's surroundings captured by a front-end camera are analyzed in real time. When a QR code of a target base station is detected in the surrounding images, the robot's current position is calculated based on data from an onboard LiDAR. If the current position is not within the preset visible area of ​​the target base station, the base station attitude relative to the robot is calculated based on the current position characteristics of the two QR codes. The actual coordinates of the target base station are calculated based on the base station attitude and the current robot position. The actual coordinates are updated to the first priority charging position, and a matching pre-parking position is calculated based on this updated position. The robot is driven to approach the pre-parking position, and after the robot's contact head connects to the base station contact head, a relay inside the robot is activated to begin charging. This invention addresses the problems in existing technologies where cleaning robots, when autonomously charging, suffer from weak positioning and anti-interference capabilities, poor environmental adaptability, and inability to accurately locate base stations, leading to charging failures, docking deviations, and low charging efficiency. It improves the adaptability of cleaning robots to complex environments, enhances the accuracy and stability of charging positioning, reduces the probability of charging failures, improves charging docking efficiency, thereby optimizing the user experience and reducing the need for manual intervention in the charging process.

[0016] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings: Figure 1 This is a schematic diagram illustrating the specific process of a charging method for a cleaning robot based on multiple sensing channels, as disclosed in an embodiment of the present invention.

[0018] Figure 2 This is a schematic diagram of the specific structure of a cleaning robot charging device based on multiple sensing channels, as disclosed in an embodiment of the present invention.

[0019] Figure 3 This is a schematic diagram of the structure of a cleaning robot based on multiple sensing channels, as disclosed in an embodiment of the present invention.

[0020] Figure 4 This is a schematic diagram of the structure of a cleaning robot charging device based on multiple sensing channels, as disclosed in an embodiment of the present invention.

[0021] Attached reference numerals: 1. Left QR code; 2. Right QR code; 3. Charging indicator light; 4 and 4', Base station communication interface; 5 and 5', Base station power interface; 6. Base station connection contact; 7. High reflective strip; 8. Horizontal bubble device; 9. Base station; 10. Left camera; 11. Right camera; 12. LiDAR; 13. Relay; 14. Body connection contact; 15. Body. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages 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 with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0023] In this invention, unless otherwise expressly specified and limited, the technical or scientific terms used herein shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in the specification and claims of this patent application do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms "an" or "a," and similar terms, do not indicate a quantity limitation, but rather indicate the presence of at least one.

[0024] In this embodiment, as shown in the appendix Figure 1 As shown, a charging method for a cleaning robot based on multi-sensor channels is disclosed, which is used to control the cleaning robot to move to a base station for charging. The base station is equipped with two QR codes identifying the base station information, and includes the following steps: Step S1: Based on the charging command, plan the charging path according to the pre-stored first priority charging position, and analyze the images around the machine collected by the front-end camera in real time while driving along the charging path; when the QR code of the target base station is found in the image around the machine, calculate the current position of the machine based on the data obtained by the vehicle-mounted LiDAR.

[0025] Based on the charging command, the pre-stored first priority charging position is retrieved. According to the first priority charging position, the charging path of the cleaning robot body to the base station is planned. The cleaning robot body is controlled to move along the planned charging path. During the movement, the front-end camera is activated to continuously collect images of the robot body's surroundings. The images of the robot body's surroundings include images of the robot body's surrounding environment. The collected images of the robot body's surroundings are analyzed and processed in real time. During the image analysis process, the dual QR code information configured by the target base station is identified. After the QR code is identified, the vehicle-mounted LiDAR is activated to collect positioning-related data. Based on the positioning data collected by the LiDAR and combined with the motion parameters of the robot body, the current spatial position of the robot body is calculated.

[0026] Step S2: If the current location of the device is not within the preset visible area of ​​the stored target base station, the base station attitude of the target base station relative to the device is calculated based on the current location features of the two parsed QR codes, and the actual coordinate position of the target base station is calculated based on the base station attitude and the current location of the device.

[0027] If the current location of the device is not within the pre-stored target base station's preset visible area, the spatial position features of the QR codes on the left and right sides of the target base station are extracted and parsed to obtain the orientation, relative spacing, and other positional features of the two QR codes in space. Based on the complete spatial position features of the two QR codes obtained from the parsing, combined with the calibration layout parameters of the two QR codes at the base station, the spatial attitude of the target base station relative to the device is calculated. The calculated spatial attitude of the target base station relative to the device is correlated with the current spatial position of the device obtained by the lidar positioning, and coordinate conversion is performed in combination with the coordinate system of the operating area map. The actual coordinate position of the target base station in the operating area map is obtained through multi-dimensional spatial coordinate calculation.

[0028] The calibration layout parameters specifically include the left and right placement of the two QR codes on the front of the base station, the fixed spacing between the two QR codes, the encoding and calibration information of the left and right QR codes respectively, the fixed encoding of the base station corresponding to the left QR code and the base station type encoding corresponding to the right QR code, the spatial position reference of the two QR codes relative to the base station charging contacts, the relative placement of the two QR codes and the base station reflective strip, the horizontal installation height of the two QR codes, the spatial orientation reference of the two QR codes relative to the base station level bubble, the center placement coordinates of the two QR codes on the front of the base station, and the installation position of the frosted acrylic plate on the outside of the two QR codes and the spacing reference of the QR codes.

[0029] In one specific embodiment, as shown in the appendix Figure 2-3 As shown, a charging indicator light 3 is configured above the base station 9. When the base station is performing a charging operation, the charging indicator light stays on. When the charging operation is completed or the base station is idle, it switches to an off state.

[0030] The base station connection contact 6 integrates base station communication interfaces 4 and 4', and base station power interfaces 5 and 5'. The cleaning robot is equipped with a body connection contact 14, which integrates a body communication interface and a body power interface. The body communication interface is located in the middle area of ​​the body connection contact and is used to achieve bidirectional communication docking with the corresponding interface of the base station. The body power interface is divided into a positive power interface and a negative power interface, which are symmetrically arranged on both sides of the body communication interface, respectively aligning with the base station power interfaces 5 and 5' to achieve precise alignment of positive and negative terminals. The body communication interface and the body power interface work together to complete the communication connection and power transmission between the cleaning robot and the base station. The overall height of the body connection contact 14 is consistent with the height of the base station connection contact 6 to ensure positional matching during docking. The cleaning robot has a built-in inertial measurement unit (IMU) for collecting its own motion perception data. Its front end is equipped with dual cameras and a lidar 12. The dual cameras, including a left camera 10 and a right camera 11, are used to collect images of the base station QR code, a bubble level, and the surrounding environment to achieve positioning, calibration, and base station identification functions. The cleaning robot's left and right wheels, as well as its front and rear wheel sets, are equipped with adjustable suspensions to adapt to horizontal offsets from the base station and its own pitch angle offsets, correcting the docking posture and ensuring docking accuracy. Simultaneously, the cleaning robot's body 15 has a built-in relay 13, primarily connecting the battery and the power supply to the contact head.

[0031] The base station is equipped with a housing, with a pre-set docking area at the front. This area contains a base station connection contact. The overall interface layout and dimensions of the base station connection contact are precisely adapted to the connection contact of the cleaning robot body. A base station communication interface and a base station power interface are also provided. The base station power interface has a positive trigger terminal and a negative trigger terminal, corresponding one-to-one with the positive and negative terminals of the cleaning robot body's power interface for precise electrical connection. The base station connection contact adopts a retractable structure, protruding from the front of the housing under normal conditions. When physical contact occurs with the connection contact of the cleaning robot body, it compresses inward along a pre-set guide structure until it is flush with the top of the contact at the front of the housing, then stops. The top of the contact is made of insulating material, achieving motion guidance, compression limiting, and short-circuit avoidance functions. The positive and negative trigger terminals of the base station power interface are symmetrically equipped with elastic reset structures on the rear side to adapt to the docking scenario of the cleaning robot tilting left and right at a preset angle, ensuring effective contact of the power interface. Both the positive and negative trigger terminals have preset lengths to reserve adaptation margin for the left and right position deviation of the cleaning robot during docking. The base station communication interface completes position adaptation synchronously with the base station power interface to ensure synchronous and accurate contact between the communication and power interfaces.

[0032] On the front of the base station housing, on the same side as the contact head connected to the base station, two QR codes are horizontally spaced, including a left QR code 1 and a right QR code 2. These codes respectively load the base station's fixed encoding information and type encoding information for the cleaning robot to accurately identify and calibrate the base station's attributes. Light sources are mounted on the sides or back of the QR codes to provide illumination and ensure effective identification in various lighting conditions. Simultaneously, two highly reflective strips 7 are horizontally spaced on the housing surface, serving as an auxiliary positioning structure in case of QR code positioning failure, completing the positioning calibration for the cleaning robot's charging docking. An observable bubble level 8 is also installed on the base station to display its current horizontal status, providing visual evidence for the cleaning robot to determine horizontal deviation. The base station has a built-in supply controller and water and wastewater storage modules, and is expanded with water replenishment and wastewater recycling interfaces. It is also equipped with a robotic arm disassembly device, a cleaning parts storage bin, and a new parts pusher, enabling the cleaning robot to replenish water, remove wastewater, and automatically replace cleaning parts. All new functional modules are compatible with the existing charging and positioning structures, and their spatial position parameters are incorporated into the QR code calibration layout parameters for precise docking with the corresponding interfaces on the cleaning robot.

[0033] Step S3: Update the actual coordinate position to the first priority charging position, and calculate the matching pre-stop position based on the updated first priority charging position; drive the machine body to approach the pre-stop position, and after the machine body connecting contact and the base station connecting contact are connected, activate the relay in the machine body to perform charging operation.

[0034] Specifically, the actual coordinate position is updated to the first priority charging position, and based on the updated first priority charging position, a matching pre-stop position is calculated in combination with the space margin for the machine's operation and the positioning accuracy requirements. The driving path is replanned according to the updated first priority charging position and the pre-stop position, and the machine is driven to approach the pre-stop position along the planned path. After the machine reaches the pre-stop position, the base station QR code information is identified again to complete the coordinate verification and calibration. Then the machine continues to approach the base station at a low speed. After the machine's connecting contact head and the base station's connecting contact head make physical contact and the communication interface establishes an effective connection, the relay inside the machine is activated. After the machine completes deceleration and braking and comes to a complete stop, the relay at the base station is activated simultaneously to establish a complete charging path and officially start the charging operation inside the machine.

[0035] In this embodiment, the body connection contact includes a body communication interface and a body power interface; the base station includes a housing and a base station connection contact installed on the front of the housing, and the base station connection contact includes a base station communication interface and a base station power interface that match the body connection contact.

[0036] Specifically, the body connection contact integrates a body communication interface and a body power interface. The body communication interface is located in the middle area of ​​the body connection contact and corresponds to the communication interface of the base station to achieve bidirectional communication docking. The body power interface is divided into a positive power interface and a negative power interface, symmetrically arranged on both sides of the body communication interface. The positive power interface is aligned with the voltage trigger positive terminal of the base station, and the negative power interface is aligned with the voltage trigger negative terminal of the base station, achieving precise alignment of positive and negative terminals. The body communication interface and the body power interface are matched one-to-one with the corresponding interfaces on the base station. The two work together. After the body and the base station complete the physical docking, the body communication interface first establishes a communication connection with the base station communication interface to realize identity verification and status interaction between devices. Then, the body power interface and the base station power interface complete the power path construction. In this way, the communication connection and power transmission between the body and the base station are realized in a coordinated manner. Moreover, the overall height of the body connection contact is consistent with the height of the retractable charging contact of the base station to ensure position matching during the docking process.

[0037] The base station is equipped with a housing, and the base station connection head is installed at the front of the housing. It is compatible with the interface specifications of the body connection head, and the base station communication interface and base station power interface are set up simultaneously to complete precise docking with the corresponding interface on the body side.

[0038] Two QR codes are configured on the base station housing on the same side as the base station connection head and arranged horizontally at intervals. The two QR codes respectively contain base station fixed encoding information and base station type encoding information. A light source that can provide illumination for the QR codes is installed on one side or the back of the QR codes. Two highly reflective strips arranged horizontally at intervals are also attached to the base station housing on the same side as the base station connection head for calibration and positioning.

[0039] Specifically, two QR codes are deployed on the surface of the base station housing on the same side as the base station connector, arranged at intervals along the horizontal direction. One QR code carries fixed base station encoding information, while the other carries base station type encoding information. The dual encoding information enables accurate identification and attribute labeling of the base station. A light source is installed on the side or back of the QR code to provide illumination to the QR code surface, ensuring effective identification of the QR code under various lighting conditions. At the same time, two highly reflective strips are attached to the surface of the base station housing on the same side as the base station connector. These highly reflective strips are arranged at intervals along the horizontal direction as an auxiliary positioning structure when the QR code positioning fails, completing the positioning calibration for charging docking.

[0040] In one embodiment, the two QR codes are configured with white background and black text. When charging at night, the front light of the cleaning robot is turned on. If the backlight of the QR code on the base station is damaged, the front light provides light for the cleaning robot to recognize the QR code. When one QR code is worn and cannot be recognized, and the other QR code cannot be effectively detected, positioning is achieved using the base station's reflective strips. Positioning is calibrated using the strong reflective strips on the left and right sides surrounding the base station's QR code, and charging is then performed. If a QR code is damaged at night and the base station's reflective strips fail to detect it, the cleaning robot stops moving, issues a stop error message, and flashes a red light. The error message is pushed to the user's mobile app. If the cleaning robot's battery level is below 15%, a push notification reminds the user to handle the error again. The QR code is generated using content encryption, and a frosted acrylic plate is placed outside the QR code to prevent glare.

[0041] In this embodiment, step S3 includes: real-time detection of the position of the machine body and the target base station; when the distance between the machine body and the target base station is lower than the connection threshold but no connection feedback between the machine body communication interface and the base station communication interface is detected, it is determined that the current charging connection has failed and the machine body is controlled to leave the pre-parking position.

[0042] Specifically, relying on lidar and front-end cameras to continuously collect environmental perception data, the relative position and distance between the aircraft and the target base station are detected in real time. When the relative distance between the aircraft and the target base station is lower than the preset connection threshold, but no connection feedback signal between the aircraft's communication interface and the base station's communication interface is still detected, the current charging connection is immediately determined to be failed. Then, a driving command is sent to the aircraft to control the aircraft to drive away from the current pre-parking position and return to the designated area to prepare for recharging and docking.

[0043] The aircraft is then guided back to the pre-parking position, and the connection status with the base station communication interface is monitored in real time. If the connection with the base station communication interface is still not detected, the aircraft will drive away again until the number of successful or failed connections exceeds a preset value, at which point the docking with the current target base station will be suspended.

[0044] The aircraft is driven back to the pre-parking position. During the movement, the connection status between the aircraft's communication interface and the base station's communication interface is continuously monitored. If it is detected that the aircraft's communication interface and the base station's communication interface have not yet established a valid communication connection, the aircraft is immediately controlled to move away from the pre-parking position again. The operation of moving to the pre-parking position and checking the communication connection status is repeated until the aircraft's communication interface and the base station's communication interface are effectively connected, or the cumulative number of charging connection failures exceeds the system's preset value. Then, the charging docking operation with the current target base station is suspended.

[0045] In this embodiment, step S3 further includes: adjusting the original first priority charging position to the second priority charging position, and updating the actual coordinate position to the first priority charging position.

[0046] Specifically, the original first priority charging position stored in the system is downgraded and adjusted to the second priority charging position. At the same time, the actual coordinate position of the base station obtained by coordinate conversion is entered into the system and updated as the new first priority charging position, thus completing the recalibration of charging position priority and the synchronous update of system coordinate information.

[0047] Based on the updated first priority charging position, a matching pre-stop position is calculated; the drive body moves closer to the pre-stop position, and after the body contactor and the base station contactor are connected, the relay inside the body is activated to perform charging.

[0048] Specifically, based on the updated first priority charging position, combined with the space margin for charging docking and positioning calibration requirements, the corresponding pre-stop position is calculated and matched. The driving trajectory is planned according to the updated first priority charging position and the pre-stop position, and the machine is driven to approach the pre-stop position obtained by the calculation and matching along the planned trajectory. After the machine reaches the pre-stop position, the position is verified, and then it approaches the base station at low speed. After the contact head of the machine and the contact head of the base station make physical contact and the communication interface is effectively connected, the relay in the machine is activated. After the machine completes deceleration and braking and comes to a complete stop, the relay at the base station is activated simultaneously to establish a complete charging path for charging operation.

[0049] If the body connection contact head and the base station connection contact head fail to connect multiple times, a second charging path is planned based on the second priority charging position, and the body is controlled to move along the second charging path to the second priority charging position.

[0050] If the contact head of the aircraft and the contact head of the base station fail to achieve a valid connection after multiple attempts, the second priority charging position that has been downgraded in the system is retrieved. Based on the second priority charging position and the environmental map of the aircraft's operating area, a second charging path is planned. After the path planning is completed, the aircraft is controlled to move along the second charging path to the second priority charging position to continue the charging docking operation.

[0051] In this embodiment, the base station is equipped with an observable level bubble device for presenting the current level status of the base station. Step S3 further includes: after the connection between the body connector and the base station connector fails, acquiring a level bubble image containing the level bubble device, locating the bubble groove using edge detection / circular detection, identifying bubble features using the Hough circle transform algorithm and projecting them onto the main axis of the bubble groove, and obtaining base station flatness evaluation data after obtaining the mapping through linear fitting.

[0052] After the connection between the body connector and the base station connector fails, the front-end camera of the body acquires a horizontal bubble image containing the horizontal bubble device. Edge detection / circle detection is performed on the acquired horizontal bubble image to complete the spatial positioning of the bubble slot of the horizontal bubble device. The Hough circle transform algorithm is used to identify the bubble features in the bubble slot. The identified bubble features are projected onto the main axis direction of the bubble slot. Linear fitting processing is performed on the projected feature data to generate a corresponding mapping relationship. Based on the mapping relationship, the base station flatness related data is calculated and extracted to obtain the base station flatness evaluation data.

[0053] The leveling bubble device is used by the user to adjust the height of the base station in all directions during installation. If the base station tilts over time, causing multiple charging failures, the cleaning robot detects the leveling bubble using its front-end camera. It locates the bubble groove using edge detection / circle detection, finds the bubble using the HoughCircles algorithm, projects it onto the main axis of the groove, and obtains a mapping through linear fitting to acquire flatness assessment data. If the base station shifts, and the shift exceeds a preset threshold, the cleaning robot alerts the user that the base station is tilted.

[0054] Meanwhile, the cleaning robot uses internal IMU data to calculate and determine whether the robot body is tilting forward or backward. The tilt angle of the robot body is related to the acceleration values ​​in three directions of the IMU. When the cleaning robot is stationary, the accelerometer estimates the acceleration values ​​separately. Where pitch_acc refers to the body pitch angle estimated by the IMU's built-in accelerometer when the cleaning robot is stationary; ax is the collected acceleration data of the cleaning robot along its own x-axis; ay is the collected acceleration data of the cleaning robot along its own y-axis; and az is the collected acceleration data of the cleaning robot along its own z-axis.

[0055] Estimated separately using the gyroscope: , where pitch_gyro is the body pitch angle estimated by the built-in gyroscope when the cleaning robot is stationary; pitch_prev is the body pitch angle of the cleaning robot estimated by the gyroscope at the previous moment; gy is the collected angular velocity data of the cleaning robot around its own y-axis; dt is the time interval between two collections of angular velocity data, i.e., the time step.

[0056] After fusion method If the cleaning robot's pitch angle is too large or too small, exceeding the set threshold, the cleaning robot will report an error and push the issue to the user's site for resolution. The pitch angle is the precise pitch angle of the cleaning robot body obtained by integrating the estimation results from the accelerometer and gyroscope through a fusion algorithm. To integrate the weighting coefficients and balance the estimation results of the gyroscope and accelerometer, thereby improving the accuracy of pitch angle calculation; pitch_gyro and pitch_acc are defined as above, representing the pitch angle of the body estimated separately by the gyroscope and accelerometer, respectively.

[0057] If the final pitch angle obtained by the cleaning robot exceeds the set threshold, the cleaning robot will report an error and push the error information to the user, who will then handle the issue on-site. Simultaneously, the base station has a built-in supply controller and water and wastewater storage modules, and is equipped with additional water and wastewater recycling interfaces. It also features a robotic arm disassembly device, a cleaning parts storage bin, and a new parts delivery device, enabling the cleaning robot to replenish water, dispose of wastewater, and automatically replace cleaning parts. All new functional modules are compatible with the existing charging and positioning structures, and their spatial position parameters are incorporated into the QR code calibration layout parameters to ensure precise interface alignment with the corresponding cleaning robot interface.

[0058] In one embodiment, for multiple cleaning robots, each robot is equipped with unique identification information and has a built-in inertial measurement unit (IMU), front-end camera, body-connecting contact head, and adjustable suspension. Each cleaning robot has a pre-set dedicated main base station and can be adapted to various types of public auxiliary base stations. It simultaneously uploads data such as its location, operating status, remaining power, remaining water volume, wastewater tank level, and cleaning component lifespan to the scheduling system in real time. It has functions for operation interruption, path replanning, error reporting, and information push. It can complete operation, resupply, and attitude adjustment according to scheduling instructions. Multiple base stations are configured as a set of base stations deployed within the operating area, each with different resupply functions, including a dedicated main base station and public auxiliary base stations. Each base station is equipped with unique identification information, a shell, a base station connecting contact head, left and right QR codes, a strong reflective strip, a level bubble device, and a functional control module. The dedicated main base station is matched and bound to the corresponding cleaning robot, possessing full-function resupply capabilities. The public auxiliary base stations are categorized by function and can realize single or combined resupply functions, while simultaneously reporting their idle status, functional status, resource balance, and level bubble status to the scheduling system in real time.

[0059] Task priorities can be assigned based on the cleaning robot's operational needs, urgency, and resource status, to achieve orderly collaborative scheduling of multiple robots and multiple base stations. Specifically, this can include the following steps.

[0060] Step S101: Collect real-time status data from multiple cleaning robots and multiple base stations. The scheduling system synchronously receives real-time status data reported by each cleaning robot and each base station, establishes a real-time status database, and updates it dynamically.

[0061] The real-time status data includes, but is not limited to, multiple of the following: the cleaning robot's self-identity information, current task type, work area, work progress, remaining power, remaining water, sewage tank level, or cleaning component lifespan reported by the cleaning robot; and multiple of the following: the identity information, functional status, idle status, resource reserves, or horizontal status reported by each base station.

[0062] Step S102: Based on the real-time status data, determine the urgency level, task type, and remaining resource status of each cleaning robot, and assign urgency level, task type level, and resource warning level. The urgency level is determined based on whether the task is an emergency or located in a critical area; the task type level is determined based on whether the task is routine cleaning, deep cleaning, or emergency cleaning; and the resource warning level is determined based on whether the remaining resources trigger a replenishment threshold.

[0063] Step S103: Combining the urgency level, demand type level, and resource warning level, set the task priority for each cleaning robot. Simultaneously, set dynamic priority adjustment rules, linking them to changes in robot resource status. When a robot's remaining resources trigger a corresponding threshold, it automatically upgrades to the corresponding priority and restores its original priority after resupply. Priority information is simultaneously updated and pushed to each robot and each base station during priority adjustments. The task priorities specifically include emergency tasks, core tasks, routine tasks, and standby resupply tasks, with priority levels decreasing sequentially. The specific classifications for each task are as follows.

[0064] The emergency task is configured for cleaning robots with extremely low remaining power, located in critical work areas, or requiring urgent cleaning of designated areas. These tasks have the highest priority, and the scheduling system exclusively allocates the best available base station to them, suspending base station usage requests from lower-priority robots to ensure rapid refueling and guarantee the execution of the emergency task.

[0065] The core task is configured to perform daily fixed area deep cleaning, and to perform tasks that trigger the replenishment threshold when the robot's remaining water volume or the cleaning parts' lifespan is insufficient and the core area operation has not been completed. The priority is secondary, and the scheduling system prioritizes scheduling the cleaning robot's dedicated main base station. If the cleaning main base station is occupied, it schedules the nearest public auxiliary base station with the same function and temporarily occupies the non-dedicated base station of the regular task cleaning robot.

[0066] The routine tasks are configured to perform daily cleaning of ordinary areas, tasks with a moderate amount of robot resources remaining and no specific time requirements; they have a low priority, and the scheduling system schedules public auxiliary base stations according to the principle of first-come, first-served and nearest matching, without occupying the base station resources of high-priority tasks.

[0067] The standby replenishment task is a replenishment task when the robot has completed all its work tasks, the remaining resources are low, and there are no new work instructions. It has the lowest priority. The scheduling system schedules idle low-load base stations. If there are no idle base stations, the cleaning robot enters the nearest standby area to queue up and connects to the idle base station in turn for replenishment after it is released.

[0068] In another embodiment, quantifying the correlation between the cleaning robot's current task and other unstarted tasks, as well as its own replenishment needs, is a core basis for optimizing task planning and improving the collaborative efficiency of multiple cleaning robots and multiple base stations. This is achieved by determining the remaining running time, required charging time, and task overlay status parameters to quantify the correlation between the cleaning robot's current task, unstarted tasks, and replenishment needs. Specifically, this includes the following steps: Step S201: Extract the core parameters of the cleaning robot's current task, other unstarted tasks, and its own replenishment needs. Retrieve the remaining running time of the current task, the task parameters of the unexecuted tasks, the charging time required for itself, and other replenishment duration from the real-time status database. At the same time, clarify the specific type of task superposition status.

[0069] Step S202: Set quantitative weights and scoring standards for each acquired parameter. In combination with the collaborative scheduling requirements of multiple cleaning robots and multiple base stations, set the weight ratio of remaining operation time, required charging time, and task superposition status.

[0070] The task overlay status has the highest weight, followed by the remaining operation time, and the required charging time is a supplementary weight. A graded scoring standard is set for each parameter. The remaining operation time is assigned a graded value according to the duration of operation that can be supported, the required charging time is assigned a graded value according to the total replenishment time, and the task overlay status is assigned a graded value according to the degree of correlation. This completes the preliminary quantitative scoring of each parameter.

[0071] Step S203: Calculate the correlation degree quantification value by weighted summation. Multiply the quantification score of each parameter by its corresponding weight and sum them to obtain the correlation degree quantification value between the current task and other unexecuted tasks and its own replenishment needs. Set the correlation degree threshold range, determine the correlation degree level according to the range of the quantification value, and push the quantification result and correlation level to the scheduling system simultaneously.

[0072] The task overlay states include: when the current task and other unexecuted tasks are in a region overlay state (i.e., the work areas of the current task and the unexecuted tasks are adjacent or overlap), the scheduling system plans a continuous path for the current task, replenishment, and unexecuted tasks based on the remaining running time of the current task, avoiding repeated back-and-forth travel between adjacent areas for the cleaning robot; when in a function overlay state (the two tasks have the same function but are unrelated in area), the scheduling system determines whether to prioritize completing the current task before executing the unexecuted tasks based on the remaining running time of the current task and the urgency of the unexecuted tasks, or adjusts the allocation of unexecuted tasks during the replenishment period of the current task to avoid overloading a single cleaning robot; when in a full overlay state (both tasks have the same area and function), the scheduling system merges the unexecuted tasks and the current task for execution, calculates the total operation time after merging based on the remaining running time of the current task, and determines whether replenishment needs to be arranged in advance; when in a no-overlay state (the two tasks are unrelated), the scheduling system schedules independently according to the task priority of the cleaning robot, avoiding conflicts only in resource allocation and base station usage, and the remaining running time of the current task only affects its own replenishment decision and does not interfere with the planning of unexecuted tasks.

[0073] The system determines the correlation between the current task and its own replenishment needs based on the matching relationship between the remaining runtime of the current task and the required charging time, thereby deciding whether to interrupt the task and when to replenish it. The system compares the remaining runtime of the current task with its remaining duration. If the remaining runtime is sufficient to complete the current task, it prioritizes completing it and then plans a replenishment path based on the required charging time and the base station's idle status. If the remaining runtime is insufficient, the current task is immediately interrupted, and replenishment is prioritized. The system prioritizes scheduling the base station with the shortest total replenishment time. After replenishment is completed, the system can quickly return to its original task area to continue executing the unfinished task. Replenishment request types include charging only, charging + water replenishment, and full-function replenishment; the triggering of replenishment requests is determined by the resource consumption of the current task.

[0074] In another embodiment, in addition to basic charging functions, the base station also has modules for water replenishment, cleaning component replacement, and wastewater removal. Specifically, these include: a water replenishment function, which refers to the base station's function of replenishing cleaning water for the cleaning robot; the base station is equipped with a clean water tank, a water replenishment interface, and a liquid level sensor. The clean water tank stores cleaning water, and the liquid level sensor provides real-time feedback on the remaining water volume; the cleaning robot is equipped with a water replenishment interface; a cleaning component replacement function, which refers to the base station's function of automatically disassembling old cleaning components and installing new cleaning components for the cleaning robot; and a wastewater removal function, which refers to the base station's function of collecting wastewater generated by the cleaning robot's operations; the base station is equipped with a wastewater tank and a wastewater collection interface.

[0075] In another embodiment, the cleaning robot loads an operating area map after power-on, the map containing manually marked base station locations and pre-charging location coordinates. Under normal conditions, the cleaning robot defaults to the base station location and pre-charging location, and sets the base station location as the first priority charging location.

[0076] If the base station experiences a horizontal offset that exceeds a threshold, base station offset information is issued. Simultaneously, measurement data from inertial devices within the vehicle are acquired, and the vehicle's forward and backward tilt state is calculated based on the inertial device measurement data. If the vehicle's pitch angle exceeds a set threshold, vehicle attitude offset information is issued.

[0077] If the flatness assessment determines that the base station has a horizontal offset and the offset exceeds the system's preset threshold, the base station offset information is generated and sent out immediately, and the base station offset information is pushed to the designated terminal simultaneously. At the same time, motion sensing data collected by the inertial measurement device inside the machine is retrieved. Based on the measurement data of the inertial measurement device, the forward and backward tilt state of the machine is calculated through data fusion. If the calculated pitch angle of the machine exceeds the system's set threshold, the machine attitude offset information is generated and sent out immediately, realizing a dual warning of abnormal conditions.

[0078] In another embodiment, if the flatness assessment determines that the base station has a horizontal offset, and the offset exceeds a preset threshold of the system, base station offset information is generated and sent out immediately, and the base station offset information is pushed to a designated terminal simultaneously. At the same time, according to the direction and amount of the horizontal offset of the base station, the suspension height of the left and right wheels of the aircraft is adjusted accordingly to adapt to the horizontal offset state of the base station. Simultaneously, motion sensing data collected by the inertial measurement device in the aircraft is retrieved, and the forward and backward tilt state of the aircraft is calculated through data fusion calculation based on the measurement data of the inertial measurement device. If the calculated pitch angle of the aircraft exceeds the system set threshold, the attitude offset information of the aircraft is generated and sent out immediately. At the same time, according to the offset angle of the pitch angle, the suspension height of the front and rear wheel sets of the aircraft is adjusted accordingly to correct the pitch attitude of the aircraft, realizing dual adjustment and early warning of abnormal attitude of the base station and the aircraft.

[0079] In this embodiment, the charging method for the cleaning robot based on multiple sensing channels further includes the following steps: if a second base station is detected in the image around the robot during operation, the base station type is obtained by parsing the QR code information on the second base station. If the base station type is compatible with the current robot's charging interface and the current robot position is not within the preset visible area of ​​the stored matching base station, the coordinates of the second base station on the map are calculated based on the two QR codes on the second base station and the current robot position, and recorded in the base station information database.

[0080] If a second base station is present in the image of the surrounding area captured by the front-end camera during the vehicle's operation, the QR code information on the second base station is extracted through image analysis, and the base station type of the second base station is obtained from the QR code encoding information. If it is determined that the base station type of the second base station is compatible with the charging interface of the current vehicle, and the current location of the vehicle is not within the preset visible area of ​​the vehicle's matching base station pre-stored by the system, then based on the spatial position characteristics of the left and right dual QR codes of the second base station, combined with the current spatial position of the vehicle obtained by laser positioning, the actual coordinate position of the second base station in the operating area map is obtained through coordinate conversion, and the actual coordinate position, along with the type, encoding, and other relevant information of the second base station, is synchronously recorded in the system's base station information database.

[0081] When the aircraft reaches the pre-parking position of the supporting base station but the supporting base station is not detected, the second base station is replaced with the supporting base station of the current aircraft, and a new charging path is re-planned and generated based on the coordinate position of the second base station; after the aircraft reaches the second base station and completes the communication connection, the identity information of the second base station is obtained and the identity information of the second base station is added to the supporting base station information of the aircraft.

[0082] When the aircraft travels to the pre-parking position corresponding to the pre-stored supporting base station, but no relevant identifiers or signals of the supporting base station are detected, the second base station already recorded in the base station information database is replaced with the current supporting base station of the aircraft. The coordinates of the second base station stored in the base station information database are retrieved, and a new charging path to the second base station is replanned and generated based on the aircraft's operating area map and positioning accuracy requirements. The aircraft is then controlled to travel along the new charging path. After the aircraft arrives at the second base station and a valid communication connection is established between the aircraft's communication interface and the second base station's communication interface, the identity information of the second base station is collected and obtained. The identity information of the second base station is synchronously added to the supporting base station information database of the aircraft, completing the update and storage of the supporting base station information.

[0083] In this embodiment, as shown in the appendix Figure 4As shown, a charging device for a cleaning robot based on multi-sensory channels is disclosed, including: a position estimation module 1, a position calculation module 2, and a charging connection module 3; wherein, the position estimation module 1 is configured to plan a charging path according to a pre-stored first priority charging position based on a charging command, and to analyze the images around the robot body collected by the front-end camera in real time during the movement along the charging path; when a QR code of a target base station is found in the image around the robot body, the current position of the robot body is estimated based on the data obtained by the vehicle-mounted LiDAR; the position calculation module 2 is configured to, if the current position of the robot body is not within the preset visible area of ​​the stored target base station, calculate the base station attitude of the target base station relative to the robot body based on the current position characteristics of the two QR codes analyzed, and calculate the actual coordinate position of the target base station based on the base station attitude and the current position of the robot body; the charging connection module 3 is configured to update the actual coordinate position to the first priority charging position, and calculate a matching pre-parking position based on the updated first priority charging position; drive the robot body to approach the pre-parking position, and after the robot body connecting contact and the base station connecting contact are connected, activate the relay inside the robot body to start the charging operation.

[0084] In this embodiment, the connection charging module is further configured to: detect the position of the host and the target base station in real time; when the distance between the host and the target base station is lower than the connection threshold but no connection feedback between the host's communication interface and the base station's communication interface is detected, determine that the current charging connection has failed and control the host to leave the pre-parking position; control the host to drive back to the pre-parking position again and detect the connection status with the base station's communication interface in real time; if no connection with the base station's communication interface is detected, drive away again until the communication connection is successful or the number of connection failures exceeds a preset value, then pause the docking with the current target base station.

[0085] In this embodiment, a robot is also disclosed, including a body on which a processor and a memory are mounted. The memory is used to store a computer program executable by the processor, wherein the processor is configured to execute the computer program in the memory to implement the steps of the multi-sensory channel-based cleaning robot charging method as described above.

[0086] In this embodiment, a computer-readable storage medium is also disclosed, which stores a computer program that, when executed by a processor, implements the steps of the multi-sensory channel-based cleaning robot charging method as described above.

[0087] If the aforementioned multi-sensor channel-based cleaning robot charging device is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various embodiments of the multi-sensor channel-based cleaning robot charging method described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not 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 of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

[0089] In summary, the above description is only a preferred embodiment of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should be covered by the present invention.

Claims

1. A charging method for a cleaning robot based on multiple sensing channels, used to control the cleaning robot to move to a base station for charging, wherein the base station is equipped with two QR codes identifying the base station information, characterized in that... Includes the following steps: S1, based on the charging command, a charging path is planned according to the pre-stored first priority charging position. During the driving along the charging path, the images around the body collected by the front-end camera are analyzed in real time. When the QR code of the target base station is found in the image around the body, the current position of the body is calculated based on the data obtained by the vehicle-mounted lidar. S2, if the current location of the machine body is not within the preset visible area of ​​the stored target base station, the base station attitude of the target base station relative to the machine body is deduced based on the current location features of the two parsed QR codes, and the actual coordinate position of the target base station is calculated based on the base station attitude and the current location of the machine body. S3, update the actual coordinate position to the first priority charging position, and calculate the matching pre-parking position based on the updated first priority charging position; The drive unit moves closer to the pre-stop position, and after the unit's connecting contact head connects to the base station's connecting contact head, the relay inside the unit is activated to perform charging operations.

2. The charging method for a cleaning robot based on multiple sensing channels according to claim 1, characterized in that: The body connection contact includes a body communication interface and a body power interface; The base station includes a housing and a base station connection contact installed on the front of the housing. The base station connection contact includes a base station communication interface and a base station power interface that are matched with the body connection contact. Two QR codes are configured on the base station housing on the same side as the base station connection head and arranged horizontally at intervals. The two QR codes respectively contain base station fixed encoding information and base station type encoding information. A light source that can provide illumination for the QR codes is installed on one side or the back of the QR codes. Two highly reflective strips arranged horizontally at intervals are also attached to the base station housing on the same side as the base station connection head for calibration and positioning.

3. The charging method for a cleaning robot based on multiple sensing channels according to claim 2, characterized in that, Step S3 includes: The position of the machine body and the target base station is detected in real time. When the distance between the machine body and the target base station is lower than the connection threshold but no connection feedback between the machine body's communication interface and the base station's communication interface is detected, it is determined that the current charging connection has failed and the machine body is controlled to move away from the pre-parking position. The aircraft is then guided back to the pre-parking position, and the connection status with the base station communication interface is monitored in real time. If the connection with the base station communication interface is still not detected, the aircraft will drive away again until the number of successful or failed connections exceeds a preset value, at which point the docking with the current target base station will be suspended.

4. The charging method for a cleaning robot based on multiple sensing channels according to claim 3, characterized in that, Step S3 further includes: The original first priority charging position is adjusted to the second priority charging position, and the actual coordinate position is updated to the first priority charging position; The matching pre-stop position is calculated based on the updated first priority charging position; the drive body moves closer to the pre-stop position, and after the body connection contact and the base station connection contact are connected, the relay inside the body is activated to perform charging operation; If the body connection contact head and the base station connection contact head fail to connect multiple times, a second charging path is planned based on the second priority charging position, and the body is controlled to move along the second charging path to the second priority charging position.

5. The charging method for a cleaning robot based on multiple sensing channels according to claim 4, characterized in that, The base station is equipped with an observable bubble level device for displaying the current horizontal state of the base station, and step S3 further includes: After the connection between the body connector and the base station connector fails, a horizontal bubble image containing the horizontal bubble device is obtained. The bubble groove is located using edge detection / circular detection. The bubble features are identified using the Hough circle transform algorithm and projected onto the main axis of the bubble groove. The base station flatness evaluation data is obtained after obtaining the mapping through linear fitting. If the base station experiences a horizontal offset that exceeds a threshold, base station offset information is issued. Simultaneously, measurement data from inertial devices within the vehicle are acquired, and the vehicle's forward and backward tilt state is calculated based on the inertial device measurement data. If the vehicle's pitch angle exceeds a set threshold, vehicle attitude offset information is issued.

6. The charging method for a cleaning robot based on multiple sensing channels according to claim 5, characterized in that, It also includes the following steps: If a second base station is detected in the image around the vehicle during operation, the base station type is obtained by parsing the QR code information on the second base station. If the base station type is compatible with the current vehicle's charging interface and the current vehicle position is not within the preset visible area of ​​the stored matching base station, the coordinates of the second base station on the map are calculated based on the two QR codes on the second base station and the current vehicle position and recorded in the base station information database. When the aircraft reaches the pre-parking position of the supporting base station but the supporting base station is not detected, the second base station is replaced with the supporting base station of the current aircraft, and a new charging path is re-planned and generated based on the coordinate position of the second base station. After the aircraft arrives at the second base station and completes the communication connection, it obtains the identity information of the second base station and adds the identity information of the second base station to the information of the base station associated with the aircraft.

7. A charging device for a cleaning robot based on multi-sensor channels, characterized in that, include: The location estimation module plans a charging path based on the charging command and the first priority charging position stored in the pre-stored data. During the driving along the charging path, it analyzes the images around the body collected by the front-end camera in real time. When the QR code of the target base station is found in the image around the body, the current position of the body is estimated based on the data obtained by the vehicle-mounted LiDAR. The location calculation module, if the current location of the device is not within the preset visible area of ​​the stored target base station, calculates the base station attitude of the target base station relative to the device based on the current location features of the two parsed QR codes, and calculates the actual coordinate position of the target base station based on the base station attitude and the current location of the device. Connect the charging module, update the actual coordinate position to the first priority charging position, and calculate the matching pre-parking position based on the updated first priority charging position; The drive unit moves closer to the pre-stop position, and after the unit's connecting contact head connects to the base station's connecting contact head, the relay inside the unit is activated to perform charging operations.

8. The charging device for a cleaning robot based on multiple sensing channels according to claim 7, characterized in that: The charging module is also configured to: The position of the machine body and the target base station is detected in real time. When the distance between the machine body and the target base station is lower than the connection threshold but no connection feedback between the machine body's communication interface and the base station's communication interface is detected, it is determined that the current charging connection has failed and the machine body is controlled to move away from the pre-parking position. The aircraft is then guided back to the pre-parking position, and the connection status with the base station communication interface is monitored in real time. If the connection with the base station communication interface is still not detected, the aircraft will drive away again until the number of successful or failed connections exceeds a preset value, at which point the docking with the current target base station will be suspended.

9. A robot, characterized in that: The device includes a body on which a processor and a memory are mounted, the memory storing a computer program executable by the processor, wherein the processor is configured to execute the computer program in the memory to implement the steps of the method as described in any one of claims 1-6.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-6.

Images