Charging control method and device of robot, electronic equipment and storage medium

Abstract

The invention provides a charging control method and device of a robot, electronic equipment and a storage medium, and relates to the technical field of robotics.The robot is provided with a solar module and an inertial navigation module, and the method comprises the steps that the illumination intensity level is set according to the charging power supply current of the solar module; setting a time level according to the time zone information and the time information; controlling the robot to move in an arch shape, and establishing a charging grid map through an inertial navigation module; if the robot triggers the charging condition, determining an optimal charging position according to the illumination intensity grade, the time grade and the charging grid map; generating a navigation path according to the optimal charging position, and controlling the robot to move to the optimal charging position to complete charging. According to the invention, the robot can be prevented from wasting battery energy under the condition that the overall illumination condition is poor, the cruising ability of the robot is remarkably improved, human intervention is reduced, and a place with strong illumination is efficiently found for charging.

Description

Technical Field

[0001] The present invention relates to the field of robot technology, and in particular to a charging control method, device, electronic equipment and storage medium for a robot. Background Art

[0002] Currently, automatic intelligent pool cleaning robots have become the first choice for many pool owners for pool cleaning solutions. With built-in intelligent systems and efficient cleaning mechanisms, these robots effectively reduce the burden of manual pool cleaning and improve the efficiency and convenience of pool maintenance. Although pool cleaning robots have greatly improved the pool cleaning process, their own maintenance and charging requirements still pose certain challenges to users.

[0003] Solar charging, as an environmentally friendly and sustainable way to supplement energy, is seen as an effective way to improve the endurance of robots. By integrating solar panels on the robot, it can provide the robot with a steady supply of electricity when there is sufficient light, thereby reducing dependence on external power sources and reducing maintenance costs. However, a major challenge faced by solar charging in practical applications is the limitation of lighting conditions. At night, in rainy weather, or when there are shelters around the swimming pool that cause insufficient light, it is difficult for the robot to obtain enough energy from the solar panels to maintain its normal operation. Therefore, how the robot can automatically find and move to a place with sufficient light for charging is an urgent problem that needs to be solved. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, the present invention provides a charging control method, device, electronic device and storage medium for a robot, which effectively solve the problem that the existing robots cannot automatically find and move to a place with sufficient light for charging.

[0005] In a first aspect, the present invention provides a charging control method for a robot, wherein the robot is provided with a solar module and an inertial navigation module, and the method comprises:

[0006] Setting the light intensity level according to the charging supply current of the solar module;

[0007] Setting time levels according to time zone information and time information;

[0008] Controlling the robot to move in an arcuate manner and establishing a charging grid map through the inertial navigation module;

[0009] If the robot triggers a charging condition, determining an optimal charging position according to the light intensity level, the time level and the charging grid map;

[0010] A navigation path is generated according to the optimal charging position, and the robot is controlled to move to the optimal charging position to complete charging.

[0011] Furthermore, the step of setting the light intensity level according to the charging power supply current of the solar module includes:

[0012] Obtaining the charging power supply current of the solar module;

[0013] Calibrate the corresponding light intensity according to the charging power supply current;

[0014] The illumination intensity level is determined according to the illumination intensity.

[0015] Further, setting the time level according to the time zone information and the time information includes:

[0016] Get the time zone information and time information of the current location;

[0017] Determine the sunrise time and sunset time of the current location according to the time zone information and the time information;

[0018] The time level is set according to the sunrise time and the sunset time.

[0019] Further, the controlling the robot to move in an arcuate manner and establishing a charging grid map through the inertial navigation module includes:

[0020] Control the robot to rotate and send ultrasonic waves to obtain the nearest target wall;

[0021] Controlling the robot to move to the target wall, and establishing a plane coordinate system with the geometric center of the robot as the origin;

[0022] Controlling the robot to move in an arc shape along one side of the target wall, and the inertial navigation module recording current position information;

[0023] The grid information is updated according to the current location information and the moving distance to obtain the charging grid map.

[0024] Furthermore, before updating the grid information according to the current position information and the moving distance, the method further includes:

[0025] Determine the reachable state of each grid according to the action trajectory of the robot;

[0026] The illumination intensity level and the time level of each of the grids are determined according to the current position information and the time information.

[0027] Further, determining the optimal charging position according to the light intensity level, the time level and the charging grid map includes:

[0028] determining a real-time light intensity level according to the real-time position of the robot;

[0029] If the real-time illumination intensity level is the maximum illumination intensity level, the real-time position is determined as the optimal charging position, otherwise the current time level is determined;

[0030] Search the charging grid map according to the real-time location to find the grid set with the highest light intensity level at the current time level;

[0031] If the light intensity level corresponding to the grid set is greater than the real-time light intensity level, then find the target grid in the grid set that is closest to the real-time position and use the target grid as the optimal charging position; otherwise, determine the real-time position as the optimal charging position.

[0032] Further, the step of searching for a target grid in the grid set that is closest to the real-time position includes:

[0033] Acquire real-time location information of the real-time location and grid location information of each grid in the grid set;

[0034] Using a path search algorithm to calculate the shortest path according to the real-time location information and the grid location information to obtain a path set;

[0035] A target path with the shortest distance is determined in the path set, and a grid corresponding to the target path is determined as the target grid.

[0036] In a second aspect, the present invention provides a charging control device for a robot, wherein the robot is provided with a solar module and an inertial navigation module, and the device comprises:

[0037] A first setting module, used for setting the light intensity level according to the charging power supply current of the solar module;

[0038] A second setting module, used for setting the time level according to the time zone information and the time information;

[0039] A map building module, used to control the robot to move in an arcuate manner and to build a charging grid map through the inertial navigation module;

[0040] a position determination module, configured to determine an optimal charging position according to the light intensity level, the time level and the charging grid map if the robot triggers a charging condition;

[0041] The charging navigation module is used to generate a navigation path according to the optimal charging position and control the robot to move to the optimal charging position to complete charging.

[0042] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the robot charging control method as described in the first aspect of the present invention.

[0043] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the robot charging control method as described in the first aspect of the present invention.

[0044] The robot charging control method, device, electronic device and storage medium provided by the present invention dynamically adjust the robot's charging strategy according to the light intensity level and time level, construct a charging grid map through bow movement and inertial navigation module, continuously improve and optimize the charging grid map, and ensure the accuracy of the map. Once the charging condition is triggered, the robot should be able to quickly select the best charging position based on the current information, generate an efficient navigation path, and control the robot to move along the path to the best charging position. The robot can avoid wasting battery energy when the overall lighting conditions are poor, significantly improve the robot's endurance, reduce human intervention, and efficiently find places with strong light for charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0046] Figure 1 This is a first schematic diagram of the process of the charging control method of the robot provided by an embodiment of the present invention;

[0047] Figure 2 is a second schematic diagram of the charging control method flow of a robot provided by an embodiment of the present invention;

[0048] Figure 3 is a third schematic diagram of the process of the charging control method of the robot provided by an embodiment of the present invention;

[0049] Figure 4 is a fourth schematic diagram of the process of the charging control method of the robot provided by an embodiment of the present invention;

[0050] Figure 5 is a schematic diagram of the bow-shaped movement in an embodiment of the present invention;

[0051] Figure 6is a fifth schematic diagram of the charging control method flow of a robot provided by an embodiment of the present invention;

[0052] Figure 7 is a sixth schematic diagram of the charging control method flow of a robot provided by an embodiment of the present invention;

[0053] Figure 8 is a schematic structural diagram of a charging control device for a robot provided in an embodiment of the present invention;

[0054] Fig. 9 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention.

[0055] Description of main component symbols:

[0056] 800, charging control device of the robot; 810, first setting module; 820, second setting module; 830, map building module; 840, location determination module; 850, charging navigation module; 900, electronic device; 910, processor; 920, communication interface; 930, memory; 940, communication bus. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be further clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. It should be noted that the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0058] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0060] Solar charging, as an environmentally friendly and sustainable way to supplement energy, is seen as an effective way to improve the endurance of robots. By integrating solar panels on the robot, it can provide the robot with a steady supply of electricity when there is sufficient light, thereby reducing dependence on external power sources and reducing maintenance costs. However, a major challenge faced by solar charging in practical applications is the limitation of lighting conditions. At night, in rainy weather, or when there are shelters around the swimming pool that cause insufficient light, it is difficult for the robot to obtain enough energy from the solar panels to maintain its normal operation. Therefore, how the robot can automatically find and move to a place with sufficient light for charging is an urgent problem that needs to be solved.

[0061] Example 1

[0062] The embodiment of the present invention provides a charging control method for a robot, which effectively solves the problem that the existing robot cannot automatically find and move to a place with sufficient light for charging. In the embodiment of the present invention, the robot may be a swimming pool cleaning robot, which is provided with a solar module and an inertial navigation module. Figure 1 is a first schematic diagram of the charging control method flow of a robot provided by an embodiment of the present invention, such as Figure 1 As shown, the method comprises the following steps:

[0063] S100: Setting a light intensity level according to a charging power supply current of a solar module.

[0064] Figure 2 is a first schematic diagram of the charging control method flow of a robot provided by an embodiment of the present invention, such as Figure 2 As shown, the setting of the light intensity level specifically includes the following steps:

[0065] S110: Obtain charging power supply current of the solar module.

[0066] Collect the output voltage of the solar module, charge the solar module according to the output voltage, and collect the charging current C of the solar module s .

[0067] S120, calibrating the corresponding light intensity according to the charging power supply current.

[0068] Calibrate the charging supply current C through preliminary tests s and light intensity L s The relationship is as follows:

[0069] L s =f(C s )

[0070] In the above formula, f(C s ) represents the functional relationship between charging supply current and light intensity.

[0071] Optionally, the light intensity may also be directly collected by installing a light intensity sensor on the robot.

[0072] S130: Determine the light intensity level according to the light intensity.

[0073] In the embodiment of the present invention, the light intensity level SL can be divided into N levels, where N is greater than or equal to 2. In the embodiment of the present invention, the light intensity level SL is divided into 4 levels, with a value range of [0, 3], increasing from 0 to 3. s Less than or equal to the first light intensity threshold L sc0 When the light intensity level SL is 0, when the light intensity L s Greater than the first light intensity threshold L sc0 and is less than or equal to the second light intensity threshold L sc1 When the light intensity level SL is 1; when the light intensity L s Greater than the second light intensity threshold L sc0 And is less than or equal to the third light intensity threshold L sc2 When the light intensity level SL is 2; when the light intensity L s Greater than the third light intensity threshold L sc2 , the light intensity level SL is 3.

[0074] According to the light intensity level, the robot's charging strategy can be dynamically adjusted. For example, during periods of high light intensity, the robot can prioritize those areas for charging to make full use of solar energy.

[0075] S200: Setting a time level according to the time zone information and the time information.

[0076] Figure 3 is a third schematic diagram of the charging control method flow of the robot provided by an embodiment of the present invention, such as Figure 3 As shown, the setting of the time level specifically includes the following steps:

[0077] S210: Obtain time zone information and time information of the current location.

[0078] Optionally, the time zone information and time information of the current location can be obtained through the Internet of Things (IoT) module.

[0079] S220: Determine the sunrise time and sunset time of the current location according to the time zone information and the time information.

[0080] In the embodiment of the present invention, the sunrise time at the current location is Td1, and the sunset time is Td2, then the daytime time period is [Td1, Td2], and the night time period is the time outside [Td1, Td2] in 24 hours of a day.

[0081] S230: Setting the time level according to the sunrise time and the sunset time.

[0082] In an embodiment of the present invention, the time level can be set according to the actual situation of the local location. For example, if the sunrise time Td1 is before 7 am and the sunset time Td2 is after 5 pm, the whole day period can be divided into 5 time levels TL from 0 to 4. The first time level TL0 is the night time period, the second time level TL1 is from sunrise time Td1 to 7 am and from 5 pm to sunset time Td2; the third time level TL2 is from 7 am to 9 am and from 3 pm to 5 pm; the fourth time level TL3 is from 9 am to 11 am and from 1 pm to 3 pm; the fifth time level TL4 is from 11 am to 1 pm.

[0083] Optionally, the time level can be simplified into two levels TL0 and TL1, TL0 represents the night time period, and TL1 represents the day time period [Td1, Td2].

[0084] By setting time levels, you can identify the times of day when light intensity is higher and duration is longer, and schedule the robot to prioritize cleaning and charging during these times.

[0085] S300, controlling the robot to move in an arc shape, and establishing a charging grid map through an inertial navigation module.

[0086] Figure 4 is a fourth schematic diagram of the charging control method flow of a robot provided by an embodiment of the present invention, such as Figure 4 As shown, the establishment of the charging grid map specifically includes the following steps:

[0087] S310, controlling the robot to rotate and send ultrasonic waves to obtain the nearest target wall.

[0088] In an embodiment of the present invention, the swimming pool cleaning robot is provided with an angle sensor and an ultrasonic sensor, which control the swimming pool cleaning robot to rotate one circle in place and send ultrasonic waves. The current angle and the distance between the forward ultrasonic wave are respectively obtained through the angle sensor and the ultrasonic sensor. The nearest target wall can be found by traversing the recorded distances.

[0089] S320, controlling the robot to move to the target wall, and establishing a plane coordinate system with the robot's geometric center as the origin.

[0090] The swimming pool cleaning robot is controlled to move toward the target wall. The target wall can be identified by setting a distance sensor or a collision sensor to assist in building a plane coordinate system. Optionally, the swimming pool cleaning robot can scan the surrounding environment and generate distance data through a distance sensor, thereby accurately measuring the distance and angle between the swimming pool cleaning robot and the target wall. By analyzing these distance data, the swimming pool cleaning robot can identify the position and contour of the target wall. The collision sensor can provide a trigger signal when the swimming pool cleaning robot collides with the target wall to detect whether a collision occurs with the target wall. The collision sensor can be contact (such as a mechanical contact) or non-contact (such as ultrasonic and infrared). Once a collision is detected, the swimming pool cleaning robot can adjust its posture to keep it parallel or vertically aligned with the target wall. Then a plane coordinate system is established with the geometric center of the swimming pool cleaning robot as the origin O, where the positive direction of the X-axis points to the front of the swimming pool cleaning robot, and the positive direction of the Y-axis is perpendicular to the X-axis and points to the right side of the swimming pool cleaning robot.

[0091] S330, controlling the robot to move in an arc shape along one side of the target wall, and the inertial navigation module records the current position information.

[0092] Figure 5 Schematic diagram of the arcuate movement in the embodiment of the present invention. Figure 5 As shown, the pool cleaning robot moves in an arch-shaped manner along one side of the target wall. To ensure coverage, the arch-shaped coverage path interval is designed to be a robot body width distance, thereby ensuring that the pool cleaning robot can cover the entire pool area more efficiently during movement.

[0093] The inertial navigation module records the current position information (x, y), establishes a grid with a resolution of Sd (a square with an area of ​​Sd) based on the current position information, and records the grid attributes during the movement, which include the reachable state, the light intensity level, and the time level. The reachable state of each grid is determined according to the robot's movement trajectory. The reachable state may include three states: the machine can pass, the machine cannot pass, and the machine has not been there. The light intensity level and time level of each grid are determined according to the current position information and time information. The time level is divided into 5 levels, and the time period represented by each level is shown in step S230. If the current time level TL is greater than 0, it is determined whether the current light intensity level is greater than the recorded light intensity level. If it is greater, the light intensity level is updated. The light intensity level SL is divided into 4 levels, SL0 indicates no light, and SL3 indicates the strongest light.

[0094] S340: Update grid information according to current location information and moving distance to obtain a charging grid map.

[0095] Optionally, when it is determined that the moving distance Δx and Δy cross the current grid to reach the next grid, the next grid information is updated and stored in a two-dimensional array until the bow-shaped movement is completed and the construction of the charging grid map is completed.

[0096] S400: If the robot triggers a charging condition, the best charging position is determined according to the light intensity level, the time level and the charging grid map.

[0097] In the embodiment of the present invention, the charging condition can be set according to the actual situation. An exemplary charging condition can be that if the power of the robot is lower than the set threshold, solar charging is required. At this time, it is determined whether the time level TL is greater than 0. If it is greater than 0, it means that it is during the daytime period and a charging location can be found for charging. If the time level TL is 0, the robot is controlled to sleep and the current time TC is obtained, and the sleep wake-up time TS is set: TC is rounded down to an integer TC i , when TC i When less than 12, TS = Td1-TC i , when TC i When greater than 12, TS = 24-TC i +Td1. When the sleep wake-up time is reached, the robot is awakened to find a charging location for charging.

[0098] Figure 6 is a fifth schematic diagram of the charging control method flow of a robot provided by an embodiment of the present invention, such as Figure 6 As shown, determining the optimal charging position includes the following steps:

[0099] S410: Determine the real-time light intensity level according to the real-time position of the robot.

[0100] The real-time light intensity level R_SLi of the current time level is recorded according to the real-time position.

[0101] S420: If the real-time light intensity level is the maximum light intensity level, the real-time position is determined as the optimal charging position; otherwise, the current time level is determined.

[0102] If the real-time light intensity level R_SLi is the maximum light intensity level, that is, the light intensity level SL is 3, the real-time position is determined as the best charging position, and the robot stays at the real-time position for charging. If the real-time light intensity level R_SLi is not 3, the current time level is determined.

[0103] S430: Search the charging grid map according to the real-time location to find the grid set with the highest light intensity level at the current time level.

[0104] S440: If the light intensity level corresponding to the grid set is greater than the real-time light intensity level, then find the target grid in the grid set that is closest to the real-time position and use the target grid as the best charging position; otherwise, the real-time position is determined as the best charging position.

[0105] Figure 7 6 is a sixth schematic diagram of the charging control method for a robot provided by an embodiment of the present invention. Figure 7 As shown, finding the target grid closest to the real-time position in the grid set includes the following steps:

[0106] S441. Acquire real-time location information of the real-time location and grid location information of each grid in the grid set.

[0107] S442: Calculate the shortest path according to the real-time location information and the grid location information using a path search algorithm to obtain a path set.

[0108] Optionally, an A-star search algorithm may be used for each grid in the grid set to find the shortest path from the real-time position to the corresponding grid, and a path set may be generated.

[0109] S443: Determine a target path with the shortest distance in the path set, and determine a grid corresponding to the target path as a target grid.

[0110] Optionally, if the light intensity level of the target grid is greater than the real-time light intensity level, the target grid is determined to be the best charging position, otherwise the light intensity level of the target grid is used as the real-time light intensity level to re-determine the time level to find the target grid.

[0111] S500: Generate a navigation path according to the optimal charging position, and control the robot to move to the optimal charging position to complete charging.

[0112] The robot charging control method provided by the embodiment of the present invention dynamically adjusts the robot's charging strategy according to the light intensity level and time level, constructs a charging grid map through bow movement and inertial navigation modules, continuously improves and optimizes the charging grid map, and ensures the accuracy of the map. Once the charging condition is triggered, the robot should be able to quickly select the best charging position based on the current information, generate an efficient navigation path, and control the robot to move along the path to the best charging position. The robot can avoid wasting battery energy when the overall lighting conditions are poor, significantly improve the robot's endurance, reduce human intervention, and efficiently find places with strong light for charging.

[0113] Example 2

[0114] Based on the same technical concept as the above method embodiment 1, the embodiment of the present invention provides a charging control device for a robot, Figure 8is a schematic diagram of the structure of a charging control device for a robot provided in an embodiment of the present invention, such as Figure 8 As shown, the charging control device 800 of the robot includes:

[0115] The first setting module 810 is used to set the light intensity level according to the charging power supply current of the solar module.

[0116] The second setting module 820 is used to set the time level according to the time zone information and the time information.

[0117] The map building module 830 is used to control the robot to move in an arc shape and to build a charging grid map through the inertial navigation module.

[0118] The location determination module 840 is used to determine the best charging location according to the light intensity level, time level and charging grid map if the robot triggers the charging condition.

[0119] The charging navigation module 850 is used to generate a navigation path according to the optimal charging position and control the robot to move to the optimal charging position to complete charging.

[0120] It can be understood that the implementation method of the robot charging control method described in the above-mentioned embodiment 1 is also applicable to this embodiment and can achieve the same technical effect, so it will not be repeated here.

[0121] Example 3

[0122] Based on the same concept, an embodiment of the present invention further provides an electronic device, Fig. 9 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention, such as Fig. 9 As shown, the electronic device 900 may include: a processor 910, a communication interface 920, a memory 930 and a communication bus 940, wherein the processor 910, the communication interface 920 and the memory 930 communicate with each other through the communication bus 940. The processor 910 may call the logic instructions in the memory 930 to execute the steps of the robot charging control method described in the above embodiments. For example, it includes:

[0123] S100: Setting a light intensity level according to a charging power supply current of a solar module.

[0124] S200, setting a time level according to the time zone information and the time information;

[0125] S300, controlling the robot to move in an arc shape, and establishing a charging grid map through an inertial navigation module;

[0126] S400, if the robot triggers a charging condition, determining an optimal charging position according to the light intensity level, the time level, and the charging grid map;

[0127] S500: Generate a navigation path according to the optimal charging position, and control the robot to move to the optimal charging position to complete charging.

[0128] The processor 910 may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0129] In addition, the logic instructions in the above-mentioned memory 930 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0130] The memory 930 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0131] Example 4

[0132] Based on the same concept, an embodiment of the present invention further provides a computer-readable storage medium, which stores a computer program, and the computer program includes at least one code segment, which can be executed by a main control device to control the main control device to implement the steps of the robot charging control method described in the above embodiments. For example, it includes:

[0133] S100: Setting a light intensity level according to a charging power supply current of a solar module.

[0134] S200, setting a time level according to the time zone information and the time information;

[0135] S300, controlling the robot to move in an arc shape, and establishing a charging grid map through an inertial navigation module;

[0136] S400, if the robot triggers a charging condition, determining an optimal charging position according to the light intensity level, the time level, and the charging grid map;

[0137] S500: Generate a navigation path according to the optimal charging position, and control the robot to move to the optimal charging position to complete charging.

[0138] Based on the same technical concept, an embodiment of the present invention further provides a computer program, which is used to implement the above method embodiment when executed by a main control device.

[0139] The computer program may be stored in whole or in part on a computer-readable storage medium packaged with the processor, or may be stored in whole or in part on a memory not packaged with the processor.

[0140] Based on the same technical concept, an embodiment of the present invention further provides a processor, which is used to implement the above method embodiment. The above processor can be a chip.

[0141] In summary, the robot charging control method, device, electronic device and storage medium provided by the present invention dynamically adjust the robot's charging strategy according to the light intensity level and time level, construct a charging grid map through bow movement and inertial navigation module, and continuously improve and optimize the charging grid map to ensure the accuracy of the map. Once the charging condition is triggered, the robot should be able to quickly select the best charging position based on the current information, generate an efficient navigation path, and control the robot to move along the path to the best charging position. The robot can avoid wasting battery energy when the overall lighting conditions are poor, significantly improve the robot's endurance, reduce human intervention, and efficiently find places with strong light for charging.

[0142] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0143] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A charging control method for a robot, characterized in that: The robot is provided with a solar module and an inertial navigation module, and the method comprises: Setting the light intensity level according to the charging supply current of the solar module; Setting time levels according to time zone information and time information; Controlling the robot to move in an arcuate manner and establishing a charging grid map through the inertial navigation module; If the robot triggers a charging condition, determining an optimal charging position according to the light intensity level, the time level and the charging grid map; A navigation path is generated according to the optimal charging position, and the robot is controlled to move to the optimal charging position to complete charging.

2. The robot charging control method according to claim 1, characterized in that: The step of setting the light intensity level according to the charging power supply current of the solar module comprises: Obtaining the charging power supply current of the solar module; Calibrate the corresponding light intensity according to the charging power supply current; The illumination intensity level is determined according to the illumination intensity.

3. The robot charging control method according to claim 1, characterized in that: The step of setting the time level according to the time zone information and the time information includes: Get the time zone information and time information of the current location; Determine the sunrise time and sunset time of the current location according to the time zone information and the time information; The time level is set according to the sunrise time and the sunset time.

4. The robot charging control method according to claim 1, characterized in that: The controlling the robot to move in an arcuate manner and establishing a charging grid map through the inertial navigation module comprises: Control the robot to rotate and send ultrasonic waves to obtain the nearest target wall; Controlling the robot to move to the target wall, and establishing a plane coordinate system with the geometric center of the robot as the origin; Controlling the robot to move in an arc shape along one side of the target wall, and the inertial navigation module recording current position information; The grid information is updated according to the current location information and the moving distance to obtain the charging grid map.

5. The robot charging control method according to claim 4, characterized in that: Before updating the grid information according to the current position information and the moving distance, the method further includes: Determine the reachable state of each grid according to the action trajectory of the robot; The illumination intensity level and the time level of each of the grids are determined according to the current position information and the time information.

6. The robot charging control method according to claim 5, characterized in that: The determining the optimal charging position according to the light intensity level, the time level and the charging grid map comprises: determining a real-time light intensity level according to the real-time position of the robot; If the real-time illumination intensity level is the maximum illumination intensity level, the real-time position is determined as the optimal charging position, otherwise the current time level is determined; Search the charging grid map according to the real-time location to find the grid set with the highest light intensity level at the current time level; If the light intensity level corresponding to the grid set is greater than the real-time light intensity level, then find the target grid in the grid set that is closest to the real-time position and use the target grid as the optimal charging position; otherwise, determine the real-time position as the optimal charging position.

7. The robot charging control method according to claim 6, characterized in that: The step of searching for a target grid in the grid set that is closest to the real-time position includes: Acquire real-time location information of the real-time location and grid location information of each grid in the grid set; Using a path search algorithm to calculate the shortest path according to the real-time location information and the grid location information to obtain a path set; A target path with the shortest distance is determined in the path set, and a grid corresponding to the target path is determined as the target grid.

8. A charging control device for a robot, characterized in that: The robot is provided with a solar module and an inertial navigation module, and the device comprises: A first setting module, used for setting the light intensity level according to the charging power supply current of the solar module; A second setting module, used for setting the time level according to the time zone information and the time information; A map building module, used to control the robot to move in an arcuate manner and to build a charging grid map through the inertial navigation module; a position determination module, configured to determine an optimal charging position according to the light intensity level, the time level and the charging grid map if the robot triggers a charging condition; The charging navigation module is used to generate a navigation path according to the optimal charging position and control the robot to move to the optimal charging position to complete charging.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: The processor executes the computer program to implement the charging control method of the robot according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the charging control method of the robot according to any one of claims 1 to 7 is implemented.

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