Positioning and control system and method for mobile charging robot

Abstract

The invention relates to a positioning and control system and method for a mobile charging robot. An acquisition device is arranged so that a user can upload charging request information containing the position of a to-be-charged electric vehicle; a processing module is arranged to send a calling instruction to a robot body closest to the position where a to-be-charged electric vehicle is located according to a sequence, and each robot body is provided with an electricity storage box, a charging execution piece, driving equipment, solar power generation equipment and a positioner. The solar power generation equipment can convert solar energy into electric energy for continuous power supply during outdoor work, and the residual solar energy can be stored, so that inconvenience caused by power failure is relieved. Besides, the positioner can obtain position information in real time and transmit the position information to the processing module, so that the dynamic state of the mobile charging robot can be mastered in real time, and the technical defect that navigation of the mobile charging robot is damaged when the mobile charging robot is in an abnormal state due to human intervention is avoided.

Description

Technical Field

[0001] The present invention relates to the field of robot control technology, and in particular to a positioning and control system and method for a mobile charging robot. Background Art

[0002] Electric vehicles (such as electric cars, electric bicycles, electric motorcycles, etc.) need to replenish electricity at specific times to maintain their normal operation. However, it is often difficult for electric vehicles to continue driving without entering a charging station. In this regard, the prior art discloses a technical solution for charging electric vehicles by controlling a mobile charging robot.

[0003] The mobile charging robot collects information about the surrounding environment through sensors, and uses control equipment to control its operation based on the obtained surrounding environment information, thereby achieving autonomous movement towards the target in an environment with obstacles and achieving the effect of charging the electric vehicle. In this process, positioning is the prerequisite for determining the position and basic posture of the mobile charging robot relative to the global coordinates in the working environment, and is the basic guarantee for the control of the mobile charging robot.

[0004] However, in the prior art, if the system of the mobile charging robot is shut down or suddenly loses power during the charging of the electric vehicle, or if the mobile charging robot is in an abnormal state due to human intervention, the navigation and mobility capabilities of the mobile charging robot will be destroyed, making it difficult to successfully complete the electric vehicle charging project. Summary of the invention

[0005] The technical problem to be solved by the present invention is how to overcome the technical defects in the prior art that the navigation and mobility capabilities of the mobile charging robot are destroyed. In order to overcome the above defects in the prior art, the present invention provides a positioning and control system and method for a mobile charging robot, including a positioning and control system for a mobile charging robot and a positioning and control method for a mobile charging robot.

[0006] The present invention provides a positioning and control system for a mobile charging robot, comprising a plurality of robot bodies, each of which is provided with a power storage box and a charging actuator, the charging actuator being electrically connected to the power storage box, and the positioning and control system further comprising:

[0007] A collection device for allowing users to upload charging request information containing the location of the electric vehicle to be charged;

[0008] A processing module is configured to sort the charging request information corresponding to different electric vehicles to be charged in order of receiving time, and send a call instruction to the robot body closest to the location of the electric vehicle to be charged according to the sorting;

[0009] A plurality of driving devices are arranged on the robot body in a one-to-one manner, and are arranged to receive a call instruction sent to the robot body, drive the robot body to move from a current position to the position of the electric vehicle to be charged using a dynamic window path planning algorithm according to the received call instruction, and then call the charging actuator to charge, and after charging is completed, continuously send a waiting-to-call signal to the processing module to indicate that the robot body is in a waiting-to-call state, and the state continues until it is called;

[0010] A plurality of solar power generation devices are arranged on the robot body in a one-to-one manner;

[0011] A plurality of positioners are arranged on the robot body in a one-to-one manner, and are used to output the position information of the robot body to the driving device and the processing module;

[0012] in,

[0013] The processing module is electrically connected to the acquisition device, and all the driving devices and all the positioners are electrically connected to the processing module;

[0014] On each of the robot bodies, the solar power generation device is electrically connected to the drive device and the positioner at the same time, the charging actuator is electrically connected to the drive device, and the drive device is electrically connected to the positioner.

[0015] The positioning and control system of the mobile charging robot disclosed in the present invention is provided with a collection device for users to upload charging request information containing the location of the electric vehicle to be charged; a processing module is provided to send a call instruction to the robot body closest to the location of the electric vehicle to be charged in order. On this basis, each robot body is provided with a power storage box, a charging actuator, a driving device, a solar power generation device and a locator. Since each robot body is provided with a solar power generation device, it can convert solar energy into electrical energy when working in the open air, and then continuously supply power, and the remaining solar energy can also be stored, so as to realize self-supply of electrical energy and alleviate the inconvenience caused by power outages. In addition, since the locator can obtain the location information in real time and can transmit the location information to the processing module, the dynamics of the mobile charging robot can be controlled in real time, avoiding the technical disadvantage that the navigation of the mobile charging robot is destroyed when the mobile charging robot is in an abnormal state due to human intervention. Moreover, since the driving device drives the robot body from its current position to the location of the vehicle to be charged using a dynamic window path planning algorithm according to the received call instruction, and the dynamic window path planning algorithm can effectively avoid obstacles on the way forward, and the algorithm complexity is low, it saves energy consumption in the process of realizing robot mobile control and realizes precise control to complete the vehicle charging task.

[0016] In a possible implementation, the processing module includes:

[0017] A generating unit is configured to receive the charging request information corresponding to the electric vehicle to be charged in real time, and sort the charging request information corresponding to different electric vehicles to be charged in order of receiving time to obtain a sorted list in real time;

[0018] A central processor is configured to issue a call instruction to the robot body closest to the location of the electric vehicle to be charged according to the sorted list;

[0019] in,

[0020] The generation unit is electrically connected to the acquisition device, and the central processing unit is electrically connected to the generation unit, all the driving devices, and all the positioners at the same time;

[0021] This solution sets up a generation unit to obtain a sorting list in real time, and then the central processor can issue a call instruction to the robot body closest to the location of the electric vehicle to be charged according to the sorting list, thereby ensuring the reasonable arrangement of the charging robots and the continuous operation of the charging project.

[0022] In a possible implementation, the central processing unit is configured to perform the following steps:

[0023] A1: taking the first electric vehicle to be charged in the sorting list as the current vehicle, and determining the location of the current vehicle according to the charging request information of the current vehicle;

[0024] A2: Find the robot body closest to the current vehicle from the robot bodies currently in the waiting state, and use this robot body as the current robot;

[0025] A3: Send a call command to the current robot to make it go to the location of the current vehicle, and retrieve the location information of the current robot in real time;

[0026] A4: Determine whether the driving device on the called robot body sends back a waiting-to-be-called signal;

[0027] If yes, then delete the charging request information corresponding to the electric vehicle to be charged recorded in the sorted list, and execute the next step when the robot body that sends back the signal to be called is called last time;

[0028] If not, proceed directly to the next step;

[0029] A5: Determine whether the content recorded in the sorting list is empty at this time;

[0030] If so, continue to judge;

[0031] If not, the next electric vehicle to be charged on the sorted list is taken as the current vehicle, and the location of the current vehicle is determined according to the charging request information of the current vehicle, and then the step A2 is executed again;

[0032] This scheme arranges charging of trams according to the order of the sorted list, and can orderly mobilize charging robots to perform charging, which not only reduces the computational complexity but also realizes the orderly calling of robots.

[0033] In a possible implementation, the driving device includes:

[0034] A camera is used to capture obstacle information in front of the robot body in real time and convert it into a grayscale image to obtain an obstacle image;

[0035] The target detection module is configured to extract the contour information of the obstacle from the obstacle image by means of encoding sampling and decoding sampling to obtain an obstacle feature map;

[0036] A driving actuator is used to drive the robot body to move according to an execution signal;

[0037] The controller is configured to send an execution signal to the driving actuator according to the obstacle feature map and the calling instruction using a dynamic window path planning algorithm to drive the robot body to move from a current position to the position of the electric vehicle to be charged, and then call the charging actuator to charge, and after charging is completed, continuously send a waiting-to-call signal to the processing module to indicate that the robot body is in a waiting-to-call state, and continue until it is called;

[0038] in,

[0039] On each of the robot bodies, the camera is electrically connected to the solar power generation device, the target detection module is electrically connected to the camera, and the controller is electrically connected to the driving actuator, the positioner, and the charging actuator at the same time;

[0040] All of the controllers are electrically connected to the processing module;

[0041] This solution can capture the obstacle information in front of the robot body through the camera during the movement of the robot body, and convert it into a grayscale image to reduce the complexity of image processing. The grayscale image is processed by the target detection module to extract the contour information of the obstacle, thereby obtaining an obstacle feature map. Subsequently, the controller calls the drive actuator to run according to the obstacle information and the call signal on the obstacle feature map to drive the robot body to move and finally complete the charging, thereby not only ensuring that the position of the robot body is controllable, but also being able to perform electric vehicle charging on the basis of reducing energy consumption.

[0042] In a possible implementation, the controller is configured to perform the following steps:

[0043] B1: Obtaining the shortest path to the location of the electric vehicle to be charged assigned by the call instruction in the feasible area according to the received call instruction through the shortest path algorithm;

[0044] B2: Determine whether there is a close obstacle based on the obstacle outline displayed on the obstacle feature map obtained at the current moment;

[0045] If so, the relative positions of all close obstacles and the robot body where the controller is located are obtained according to the position of the center of the obstacle contour extracted on the obstacle feature map, and then the next step is executed;

[0046] If not, calling the driving actuator to drive the robot body where the controller is located to continue moving forward along the shortest path, and then continue to determine whether there is an obstacle;

[0047] B3: using the relative position of all the close-range obstacles and the robot body where the controller is located to determine whether there is a vehicle to be charged assigned by the call instruction among the close-range obstacles;

[0048] If yes, go to step B7;

[0049] If not, proceed to the next step;

[0050] B4: setting a plurality of different strategies for avoiding all close-range obstacles within a predetermined time according to the relative positions of all close-range obstacles and the robot body where the controller is located, each strategy requiring the robot body where the controller is located to travel at a constant speed within a predetermined time at a speed specified by the strategy, and then executing the next step;

[0051] B5: Obtain the avoidance evaluation function values ​​of all strategies in step B4, select the strategy with the largest avoidance evaluation function value as the avoidance strategy, and then execute the next step;

[0052] B6: calling the driving actuator according to the obtained avoidance strategy to drive the robot body where the controller is located to avoid the close-range obstacle within a predetermined time, and then turning around to execute step B2;

[0053] B7: judging whether the condition for the charging actuator to be charged is met according to the relative position of the electric vehicle to be charged assigned by the calling instruction and the robot body where the controller is located;

[0054] If yes, the charging execution component is called to charge, and then the next step is executed;

[0055] If not, the driving actuator is called to drive the robot body where the controller is located to move along the location of the charging interface of the electric vehicle to be charged assigned by the calling instruction, and then continue to determine whether the conditions for the charging actuator to charge are met;

[0056] B8: Determine whether charging is completed;

[0057] If yes, then continue to send a waiting-to-be-called signal to the processing module;

[0058] If not, continue to judge;

[0059] The controller corresponding to the dynamic window path planning algorithm that executes the above steps can send an execution signal to the driving actuator according to the obstacle feature map and the call instruction, thereby driving the robot body to move from the current position to the position of the electric vehicle to be charged, and then call the charging actuator for charging, and after charging is completed, continuously send a waiting-to-call signal to the processing module to indicate that the robot body is in a waiting-to-call state, thereby realizing precise controllable position and state of the robot body.

[0060] In a possible implementation manner, in step B2, the process of determining whether there is a close obstacle is as follows:

[0061] B21: calculating the projection distance along the front direction between each obstacle and the robot body where the controller is located according to the position of the contour center of each obstacle displayed on the obstacle feature map currently obtained on the obstacle feature map;

[0062] B22: Determine whether there is an obstacle whose projection distance is less than a threshold;

[0063] If yes, it is considered that there is a close obstacle, and all obstacles with a projection distance less than the threshold are marked as close obstacles;

[0064] If not, it is deemed that there are no close obstacles;

[0065] This solution can more accurately obtain the number and position information of close-range obstacles, and thus can accurately avoid obstacles while the robot body is moving, thus avoiding collision accidents.

[0066] In a possible implementation, in step B5, the calculation formula for obtaining the avoidance evaluation function values ​​of all strategies is as follows:

[0067]

[0068] In the formula,

[0069] p i Represents the avoidance evaluation function value of the i-th strategy;

[0070] t0 represents the current moment;

[0071] T represents the predetermined time set in step B4;

[0072] represents the x component of the velocity of the robot body where the controller is located within a predetermined time as specified by the i-th strategy;

[0073] represents the y component of the velocity of the robot body where the controller is located within a predetermined time as specified by the i-th strategy;

[0074] represents the x component of the velocity of the jth close obstacle;

[0075] Represents the y component of the velocity of the jth close obstacle;

[0076] n represents the number of close obstacles;

[0077] The use of the avoidance evaluation function in the above form not only reduces the computational complexity, but also can accurately obtain the risk of collision accidents that may be caused by different strategies, thereby further achieving effective avoidance of obstacles.

[0078] In a possible implementation, the solar power generation equipment includes a focusing lens barrel and a solar cell panel which are sequentially arranged along the direction of sunlight propagation, the focusing lens barrel includes a light pipe, a filter and a focusing lens, the filter and the focusing lens are both arranged on the light pipe and sequentially arranged along the direction of sunlight propagation, and the solar cell panel is electrically connected to the camera and the positioner at the same time; this solution can filter out invalid stray light by setting a filter, thereby improving power generation efficiency and accuracy and ensuring self-sufficiency in electrical energy.

[0079] In a possible implementation, the positioning and control system further includes a lithium battery and a selector, the selector being configured to call the solar panel to be electrically connected to the camera and the locator when the voltage output by the solar panel is not less than a threshold voltage; and to call the lithium battery to be electrically connected to the camera and the locator when the voltage output by the solar panel is less than a threshold voltage, the first pin of the selector being electrically connected to the solar panel, the second pin of the selector being electrically connected to the lithium battery, and the third pin of the selector being electrically connected to the camera and the locator at the same time; thereby being able to provide continuous power for the movement or state change of the robot body, thereby further reducing the risk of power outages.

[0080] Another technical solution of the present invention is to provide a positioning and control method of a mobile charging robot, the method comprising the following steps:

[0081] S1: The user uploads the charging request information containing the location of the electric vehicle to be charged through the collection device;

[0082] S2: receiving the charging request information through a processing module, and sending a call instruction to the robot body closest to the location of the electric vehicle to be charged;

[0083] S3: receiving a call instruction sent to the robot body through a body driving device on the robot body closest to the location of the electric vehicle to be charged, and driving the robot body to move from the current position to the location of the electric vehicle to be charged by a dynamic window path planning algorithm according to the received call instruction;

[0084] S4: calling the charging actuator to charge through the driving device on the robot body closest to the location of the electric vehicle to be charged, and continuously sending a waiting-to-call signal to the processing module after charging is completed to indicate that the robot body is in a waiting-to-call state.

[0085] The method disclosed in the present invention can not only alleviate the risk of power outages during the operation of the robot and ensure the efficient and orderly charging of the electric vehicle, but also avoid the technical disadvantage that the navigation of the mobile charging robot is destroyed when the mobile charging robot is in an abnormal state due to human intervention, thereby achieving the technical effect of continuous charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Figure 1 A schematic diagram of the structure of a positioning and control system of a mobile charging robot disclosed in an embodiment of the present invention;

[0087] Figure 2 The operation flow chart of the central processing unit disclosed in the embodiment of the present invention;

[0088] Figure 3 This is an operation flow chart of the controller disclosed in the embodiment of the present invention;

[0089] Figure 4 A schematic diagram of determining the projection distance between an obstacle and a robot body where a controller is located along the front direction disclosed in an embodiment of the present invention;

[0090] Figure 5 It is a schematic diagram of the structure of the focusing lens barrel disclosed in the embodiment of the present invention;

[0091] Figure 6 The present invention is a flowchart of a method disclosed in an embodiment of the present invention.

[0092] Description of reference numerals:

[0093] 1. Light pipe, 2. Filter, 3. Focusing lens. DETAILED DESCRIPTION

[0094] First, those skilled in the art should understand that these implementations are only used to explain the technical principles of the embodiments of the present application, and are not intended to limit the protection scope of the embodiments of the present application. Those skilled in the art can make adjustments to them as needed to adapt to specific application scenarios.

[0095] In the description of the embodiments of the present application, it should be noted that, unless otherwise clearly specified and limited, the terms "electrical connection" and "electrical connection relationship" should be understood in a broad sense, that is, referring to a connection method with an electrical relationship, for example, it can be a circuit connection through a conductive wire, or it can be an electrical connection through a radio signal channel (channel), or a combination of the two. In addition, "electrical connection" and "electrical connection relationship" can be based on mechanical connection (such as a conductive wire set in a connecting key); it can be a direct connection or an indirect connection through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific circumstances.

[0096] In the embodiments of the present application, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0097] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0098] See also Figure 1 As shown, the embodiment of the present application discloses a positioning and control system for a mobile charging robot. Figure 1 As a structural diagram, the positioning and control system includes a collection device, a processing module, multiple robot bodies, multiple power storage boxes, multiple charging actuators, multiple driving devices, multiple solar power generation devices, multiple positioners, multiple selectors and multiple lithium batteries. Each robot body is provided with at least one power storage box, a charging actuator, a driving device, a solar power generation device, a positioner, a lithium battery and a selector. On each robot body, the solar power generation device is electrically connected to the driving device and the positioner at the same time, the charging actuator is electrically connected to the driving device, the driving device is electrically connected to the positioner, the charging actuator is electrically connected to all power storage boxes, the first pin of the selector is electrically connected to the solar power generation device, the second pin of the selector is electrically connected to the lithium battery, and the third pin of the selector is electrically connected to the driving device and the positioner at the same time. The processing module is electrically connected to the collection device, and all driving devices and all positioners are electrically connected to the processing module.

[0099] In this positioning and control system, the acquisition device is used for users to upload charging request information containing the location of the electric vehicle to be charged. In this embodiment, the acquisition device is composed of an information acquisition terminal and a communication module set on a mobile device. The information acquisition terminal can establish a connection with a navigation module such as Amap to obtain location information. The user uploads the charging request information through the information acquisition terminal. The charging request information contains the location and vehicle characteristics (such as license plate, charging port location, etc.). The charging request information is then transmitted to the processing module through the communication module.

[0100] See also Figure 1 In the positioning and control system, the processing module is configured to sort the charging request information corresponding to different electric vehicles to be charged in the order of receiving time, and send a call instruction to the robot body closest to the location of the electric vehicle to be charged according to the order. In this embodiment, the processing module includes a generation unit and a central processing unit. The generation unit is electrically connected to the information collection end through the communication module, and the central processing unit is electrically connected to the generation unit, all driving devices, and all locators at the same time.

[0101] In the processing module, the generation unit is configured to receive the charging request information corresponding to the electric vehicle to be charged in real time, and sort the charging request information corresponding to different electric vehicles to be charged in the order of receiving time to obtain a sorted list in real time. The central processing unit is configured to issue a call instruction to the robot body closest to the location of the electric vehicle to be charged according to the sorted list. Specifically, see Figure 2 In this embodiment, the CPU is configured to perform the following steps:

[0102] A1: The first electric vehicle to be charged in the sorting list is taken as the current vehicle, and the location of the current vehicle is determined according to the charging request information of the current vehicle;

[0103] A2: Find the robot body closest to the current vehicle from the robot bodies currently in the waiting state, and use this robot body as the current robot;

[0104] A3: Send a call command to the current robot to make it go to the location of the current vehicle, and retrieve the location information of the current robot in real time;

[0105] A4: Determine whether the driving device on the robot body being called sends back a waiting-to-call signal;

[0106] If yes, delete the charging request information corresponding to the electric vehicle to be charged that was executed by the robot body that sends back the signal to be called last time, and then execute the next step;

[0107] If not, proceed directly to the next step;

[0108] A5: Determine whether the content recorded in the sorting list is empty;

[0109] If so, continue to judge;

[0110] If not, the next electric vehicle to be charged on the sorted list is taken as the current vehicle, and the location of the current vehicle is determined according to the charging request information of the current vehicle, and then the step A2 is executed again.

[0111] See also Figure 1 In this positioning and control system, the driving device on the robot body is configured to receive a call instruction sent to the robot body where the driving device is located, and according to the received call instruction, the robot body is driven from the current position to the position of the electric vehicle to be charged using a dynamic window path planning algorithm, and then the charging actuator is called for charging, and after the charging is completed, a waiting-to-call signal is continuously sent to the processing module to indicate that the robot body is in a waiting-to-call state, and this continues until it is called.

[0112] Please continue to see Figure 1 In this embodiment, the driving device includes a camera, a target detection module, a driving actuator and a controller. On each robot body, the camera is electrically connected to the solar power generation device, the target detection module is electrically connected to the camera, and the controller is electrically connected to the driving actuator, the positioner, and the charging actuator at the same time; in addition, the controller is electrically connected to the processing module through a communication protocol interface.

[0113] In the driving device, the camera uses a high-definition black and white camera to capture the obstacle information in front of the robot body in real time and convert it into a grayscale image to obtain an obstacle image. The camera is set on the robot body, with its axis parallel to the ground and facing straight ahead.

[0114] In the driving device, the target detection module is configured to extract the contour information of the obstacle from the obstacle image by encoding sampling and decoding sampling to obtain the obstacle feature map. The target detection module in this embodiment is a target detection network composed of an encoder, a decoder and a detection head module. The obstacle image is first convolutionally encoded by the encoder, then sampled and decoded by the decoder, and finally the obstacle contour is extracted by the detection head module to obtain the obstacle feature map. In this embodiment, the mean square error loss function is used to optimize the parameters of the target detection module.

[0115] In the driving device, the driving actuator is used to drive the robot body to move according to the execution signal. Specifically in this embodiment, the driving actuator includes a motor and a wheel, and the wheel is arranged at the bottom of the robot body as a walking part, and the robot body is driven to move by the motor driving the wheel to rotate. This technology is a prior art and will not be elaborated in detail here.

[0116] In the driving device, the controller is configured to send an execution signal to the driving actuator based on the obstacle feature map and the calling instruction using a dynamic window path planning algorithm to drive the robot body where the controller is located to move from the current position to the position of the tram to be charged, and then call the charging actuator for charging, and after the charging is completed, continuously send a waiting-to-call signal to the processing module to indicate that the robot body is in a waiting-to-call state, and continue until it is called.

[0117] Specifically, see Figure 3 In this embodiment, the controller is configured to perform the following steps:

[0118] B1: Obtain the shortest path to the location of the electric vehicle to be charged assigned by the call instruction within the feasible area according to the received call instruction through the shortest path algorithm.

[0119] In order to simplify the calculation and save energy, the shortest path algorithm used in this embodiment obtains the shortest path in the following process: first, multiple groups of trajectories are found in the feasible area, and then these trajectories are evaluated, and the speed corresponding to the optimal trajectory is selected to drive the robot body to move.

[0120] B2: Determine whether there is a close obstacle based on the obstacle outline displayed on the obstacle feature map obtained at the current moment;

[0121] If so, the relative positions of all close obstacles and the robot body where the controller is located are obtained according to the position of the center of the obstacle contour extracted on the obstacle feature map, and then the next step is executed;

[0122] If not, the driving actuator is called to drive the robot body where the controller is located to continue moving forward along the shortest path, and then continue to determine whether there are obstacles.

[0123] In this step, the process of determining whether there is a close obstacle is as follows:

[0124] B21: Calculate the projection distance along the front direction between each obstacle and the robot body where the controller is located according to the pixel position on the obstacle feature map where the contour center of each obstacle displayed on the currently obtained obstacle feature map is located.

[0125] See also Figure 4 As shown, the calculation formula for calculating the projection distance between each obstacle and the robot body where the controller is located along the front direction is as follows:

[0126] d k =H0+kH k ,

[0127] In the formula,

[0128] d k Represents the projection distance between the kth obstacle and the robot body where the controller is located along the forward direction;

[0129] k represents the scale of the obstacle feature map;

[0130] H k represents the pixel height of the center of the contour representing the kth obstacle;

[0131] H0 represents the straight-line distance between the real space position corresponding to the intersection of a straight line passing through the image center of the obstacle feature map and parallel to the height direction of the obstacle feature map and the bottom edge of the obstacle feature map and the robot body.

[0132] The parameter H0 is measured by experiment. Figure 4 As shown, Figure 4 The red box in represents the obstacle feature map, H represents the pixel height, W represents the pixel width, and the straight line L represents the straight line passing through the image center point O of the obstacle feature map and parallel to the height direction of the obstacle feature map. The straight line distance between the intersection point P of the straight line L and the W axis and the position of the point in the real space and the robot body is the parameter H0. The value of the parameter H0 minus the height of the camera from the ground can be measured by a technician in this field through experiments.

[0133] B22: Determine whether there is an obstacle whose projection distance is less than a threshold;

[0134] If yes, it is considered that there is a close obstacle, and all obstacles with a projection distance less than the threshold are marked as close obstacles;

[0135] If not, it is deemed that there are no close obstacles.

[0136] B3: Use the relative position of all close-range obstacles and the robot body where the controller is located to determine whether there is a vehicle to be charged assigned by the call instruction among the close-range obstacles;

[0137] If yes, go to step B7;

[0138] If not, proceed to the next step.

[0139] Specifically, in this embodiment, the relative position of the close-range obstacle and the robot body where the controller is located is determined as follows: for the jth close-range obstacle, the relative position of the close-range obstacle and the robot body where the controller is located is calculated as follows:

[0140] (x j ,y j )=(H0+kW j , H0+kH j ),

[0141] In the formula,

[0142] x j ,y j ) represents the relative position coordinates of the jth close obstacle and the robot body where the controller is located;

[0143] W j Represents the pixel width of the center of the outline of the jth close obstacle;

[0144] H j Represents the pixel height of the center of the silhouette of the jth close obstacle.

[0145] After obtaining the relative position coordinates of all close obstacles and the robot body where the controller is located, the 2-norm of each coordinate is calculated respectively, and then it is determined whether there is a 2-norm smaller than the set value. If not, it is determined that there is no vehicle to be charged assigned by the call instruction; if so, the outline of the close obstacle with a 2-norm smaller than the set value is compared with the outline of the vehicle. If they are the same, it is determined that there is a vehicle to be charged assigned by the call instruction; otherwise, it is determined that there is no vehicle to be charged assigned by the call instruction.

[0146] B4: According to the relative positions of all close-range obstacles and the robot body where the controller is located, multiple different strategies are set to avoid all close-range obstacles within a predetermined time. Each strategy requires the robot body where the controller is located to travel at a constant speed within a predetermined time at the speed specified by the strategy, and then execute the next step;

[0147] B5: Obtain the avoidance evaluation function values ​​of all strategies in step B4, select the strategy with the largest avoidance evaluation function value as the avoidance strategy, and then execute the next step.

[0148] Specifically, in step B5, the calculation formula for obtaining the avoidance evaluation function value of all strategies is as follows:

[0149]

[0150] In the formula,

[0151] p i Represents the avoidance evaluation function value of the i-th strategy;

[0152] t0 represents the current moment;

[0153] T represents the predetermined time set in step B4;

[0154] represents the x component of the velocity of the robot body where the controller specified by the i-th strategy is located within the predetermined time;

[0155] represents the y component of the velocity of the robot body where the controller specified by the i-th strategy is located within the predetermined time;

[0156] represents the x component of the velocity of the jth close obstacle;

[0157] Represents the y component of the velocity of the jth close obstacle;

[0158] n represents the number of close obstacles.

[0159] For the jth close obstacle movement speed, the calculation formula is:

[0160]

[0161] In the formula,

[0162] ΔW j ΔH represents the change in the pixel width of the center of the jth close obstacle’s contour within the sampling time ΔT; j Represents the change in the pixel height of the center of the contour of the jth close obstacle within the sampling time ΔT.

[0163] B6: According to the obtained avoidance strategy, the driving actuator is called to drive the robot body where the controller is located to avoid the close-range obstacle within a predetermined time, and then turn around to execute step B2.

[0164] B7: judging whether the conditions for charging the charging actuator are met according to the relative positions of the electric vehicle to be charged assigned by the calling instruction and the robot body where the controller is located;

[0165] If yes, the charging execution component is called to charge, and then the next step is executed;

[0166] If not, the driving executive component is called to drive the robot body where the controller is located to move along the location of the charging interface of the electric vehicle to be charged assigned by the calling instruction, and then continue to determine whether the conditions for the charging executive component to charge are met.

[0167] B8: Determine whether charging is completed;

[0168] If so, a waiting-to-be-called signal is continuously sent to the processing module;

[0169] If not, continue judging.

[0170] In the positioning and control system, the solar power generation equipment includes a focusing lens tube and a solar cell panel arranged in sequence along the propagation direction of sunlight, see Figure 5 The focusing lens barrel includes a light pipe 1, a filter 2 and a focusing lens 3. The filter 2 and the focusing lens 3 are both arranged on the light pipe 1 and arranged in sequence along the propagation direction of sunlight. The solar cell panel is electrically connected to the camera and the locator at the same time.

[0171] In the positioning and control system, the selector is configured to call the solar panel to be electrically connected to the camera and the locator when the voltage output by the solar panel is not less than the threshold voltage; and to call the lithium battery to be electrically connected to the camera and the locator when the voltage output by the solar panel is less than the threshold voltage.

[0172] The following will further disclose the positioning and control method of the mobile charging robot corresponding to the positioning and control system of the mobile charging robot in this embodiment, see Figure 6 , the method comprises the following steps:

[0173] S1: The user uploads the charging request information containing the location of the electric vehicle to be charged through the collection device;

[0174] S2: receiving charging request information through the processing module and sending a call instruction to the robot body closest to the location of the electric vehicle to be charged;

[0175] S3: receiving a call instruction sent to the robot body through a body driving device on the robot body closest to the location of the electric vehicle to be charged, and driving the robot body to move from the current position to the location of the electric vehicle to be charged by a dynamic window path planning algorithm according to the received call instruction;

[0176] S4: calling the charging actuator to charge the robot body through the driving device on the robot body closest to the location of the electric vehicle to be charged, and continuously sending a waiting-to-call signal to the processing module after charging is completed to indicate that the robot body is in a waiting-to-call state.

[0177] The positioning and control system of the mobile charging robot disclosed in this embodiment is provided with a collection device for users to upload charging request information containing the location of the electric vehicle to be charged; and a processing module is provided to send a call instruction to the robot body closest to the location of the electric vehicle to be charged in order. On this basis, each robot body is provided with a power storage box, a charging actuator, a driving device, a solar power generation device, a selector, a lithium battery and a locator. Since each robot body is provided with a solar power generation device and a lithium battery, and the electric energy is distributed through the selector, the solar energy can be converted into electric energy when working in the open air, and then the power supply can be continuously provided. The remaining solar energy can also be stored, so as to realize the self-supply of electric energy and alleviate the inconvenience caused by power outages. In addition, since the locator can obtain the position information in real time and can transmit the position information to the processing module, the dynamics of the mobile charging robot can be controlled in real time, avoiding the technical disadvantage that the navigation of the mobile charging robot is destroyed when the mobile charging robot is in an abnormal state due to human intervention. Moreover, since the driving device drives the robot body from its current position to the location of the vehicle to be charged using a dynamic window path planning algorithm according to the received call instruction, and the dynamic window path planning algorithm can effectively avoid obstacles on the way forward, and the algorithm complexity is low, it saves energy consumption in the process of realizing robot mobile control and realizes precise control to complete the vehicle charging task.

[0178] In the description of the embodiments of the present application, it should be noted that in the description of the present application, terms such as "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is only for the convenience of description, and does not indicate or imply that the device or component must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present application.

[0179] In the description of the present application, the description with reference to the terms "one embodiment", "some embodiments", "in the present embodiment", "specific example", or "some examples" etc. means that the specific features, mechanisms, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, mechanisms, materials or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0180] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A positioning and control system for a mobile charging robot, comprising a plurality of robot bodies, each of which is provided with a power storage box and a charging actuator, wherein the charging actuator is electrically connected to the power storage box, characterized in that: The positioning and control system also includes: A collection device for allowing users to upload charging request information containing the location of the electric vehicle to be charged; A processing module is configured to sort the charging request information corresponding to different electric vehicles to be charged in order of receiving time, and send a call instruction to the robot body closest to the location of the electric vehicle to be charged according to the order; A plurality of driving devices are arranged on the robot body in a one-to-one manner, and are arranged to receive a call instruction sent to the robot body, drive the robot body to move from a current position to the position of the electric vehicle to be charged using a dynamic window path planning algorithm according to the received call instruction, and then call the charging actuator to charge, and after charging is completed, continuously send a waiting-to-call signal to the processing module to indicate that the robot body is in a waiting-to-call state, and the state continues until it is called; A plurality of solar power generation devices are arranged on the robot body in a one-to-one manner; A plurality of positioners are arranged on the robot body in a one-to-one manner, and are used to output the position information of the robot body to the driving device and the processing module; in, The processing module is electrically connected to the acquisition device, and all the driving devices and all the positioners are electrically connected to the processing module; On each of the robot bodies, the solar power generation device is electrically connected to the drive device and the positioner at the same time, the charging actuator is electrically connected to the drive device, and the drive device is electrically connected to the positioner.

2. The positioning and control system of the mobile charging robot according to claim 1, characterized in that: The processing module comprises: A generating unit is configured to receive the charging request information corresponding to the electric vehicle to be charged in real time, and sort the charging request information corresponding to different electric vehicles to be charged in order of receiving time to obtain a sorted list in real time; A central processor is configured to issue a call instruction to the robot body closest to the location of the electric vehicle to be charged according to the sorted list; in, The generation unit is electrically connected to the acquisition device, and the central processing unit is electrically connected to the generation unit, all the driving devices, and all the positioners at the same time.

3. The positioning and control system of the mobile charging robot according to claim 2, characterized in that: The central processing unit is configured to perform the following steps: A1: taking the first electric vehicle to be charged in the sorting list as the current vehicle, and determining the location of the current vehicle according to the charging request information of the current vehicle; A2: Find the robot body closest to the current vehicle from the robot bodies currently in the waiting state, and use this robot body as the current robot; A3: Send a call command to the current robot to make it go to the location of the current vehicle, and retrieve the location information of the current robot in real time; A4: Determine whether the driving device on the called robot body sends back a waiting-to-be-called signal; If yes, then delete the charging request information corresponding to the electric vehicle to be charged recorded in the sorted list, and execute the next step when the robot body that sends back the signal to be called is called last time; If not, proceed directly to the next step; A5: Determine whether the content recorded in the sorting list is empty at this time; If so, continue judging; If not, the next electric vehicle to be charged on the sorted list is taken as the current vehicle, and the location of the current vehicle is determined according to the charging request information of the current vehicle, and then the step A2 is executed again.

4. The positioning and control system of the mobile charging robot according to any one of claims 1 to 3, characterized in that: The driving device comprises: A camera is used to capture obstacle information in front of the robot body in real time and convert it into a grayscale image to obtain an obstacle image; The target detection module is configured to extract the contour information of the obstacle from the obstacle image by means of encoding sampling and decoding sampling to obtain an obstacle feature map; A driving actuator is used to drive the robot body to move according to an execution signal; The controller is configured to send an execution signal to the driving actuator according to the obstacle feature map and the calling instruction using a dynamic window path planning algorithm to drive the robot body to move from a current position to the position of the electric vehicle to be charged, and then call the charging actuator to charge, and after charging is completed, continuously send a waiting-to-call signal to the processing module to indicate that the robot body is in a waiting-to-call state, and continue until it is called; in, On each of the robot bodies, the camera is electrically connected to the solar power generation device, the target detection module is electrically connected to the camera, and the controller is electrically connected to the driving actuator, the positioner, and the charging actuator at the same time; All the controllers are electrically connected to the processing module.

5. The positioning and control system of the mobile charging robot according to claim 4, characterized in that: The controller is configured to perform the following steps: B1: Obtaining the shortest path to the location of the electric vehicle to be charged assigned by the call instruction in the feasible area according to the received call instruction through the shortest path algorithm; B2: Determine whether there is a close obstacle based on the obstacle outline displayed on the obstacle feature map obtained at the current moment; If so, the relative positions of all close obstacles and the robot body where the controller is located are obtained according to the position of the center of the obstacle contour extracted on the obstacle feature map, and then the next step is executed; If not, calling the driving actuator to drive the robot body where the controller is located to continue moving forward along the shortest path, and then continue to determine whether there is an obstacle; B3: using the relative position of all the close-range obstacles and the robot body where the controller is located to determine whether there is a vehicle to be charged assigned by the call instruction among the close-range obstacles; If yes, proceed to step B7; If not, proceed to the next step; B4: setting a plurality of different strategies for avoiding all close-range obstacles within a predetermined time according to the relative positions of all close-range obstacles and the robot body where the controller is located, each strategy requiring the robot body where the controller is located to travel at a constant speed within a predetermined time at a speed specified by the strategy, and then executing the next step; B5: Obtain the avoidance evaluation function values ​​of all strategies in step B4, select the strategy with the largest avoidance evaluation function value as the avoidance strategy, and then execute the next step; B6: calling the driving actuator according to the obtained avoidance strategy to drive the robot body where the controller is located to avoid the close-range obstacle within a predetermined time, and then turning around to execute step B2; B7: judging whether the condition for the charging actuator to be charged is met according to the relative position of the electric vehicle to be charged assigned by the calling instruction and the robot body where the controller is located; If yes, the charging execution component is called to charge, and then the next step is executed; If not, the driving actuator is called to drive the robot body where the controller is located to move along the location of the charging interface of the electric vehicle to be charged assigned by the calling instruction, and then continue to determine whether the conditions for the charging actuator to charge are met; B8: Determine whether charging is completed; If yes, then continue to send a waiting-to-be-called signal to the processing module; If not, continue judging.

6. The positioning and control system of the mobile charging robot according to claim 5, characterized in that: In step B2, the process of determining whether there is a close obstacle is as follows: B21: calculating the projection distance along the front direction between each obstacle and the robot body where the controller is located according to the position of the contour center of each obstacle displayed on the obstacle feature map currently obtained on the obstacle feature map; B22: Determine whether there is an obstacle whose projection distance is less than a threshold; If yes, it is considered that there is a close obstacle, and all obstacles with a projection distance less than the threshold are marked as close obstacles; If not, it is deemed that there are no close obstacles.

7. The positioning and control system of the mobile charging robot according to claim 5 or 6, characterized in that: In step B5, the calculation formula for obtaining the avoidance evaluation function value of all strategies is as follows: In the formula, p i Represents the avoidance evaluation function value of the i-th strategy; t0 represents the current moment; T represents the predetermined time set in step B4; represents the x component of the velocity of the robot body where the controller is located within a predetermined time as specified by the i-th strategy; represents the y component of the velocity of the robot body where the controller is located within a predetermined time as specified by the i-th strategy; represents the x component of the velocity of the jth close obstacle; Represents the y component of the velocity of the jth close obstacle; n represents the number of close obstacles.

8. The positioning and control system of the mobile charging robot according to claim 7 is characterized in that: The solar power generation equipment comprises a focusing lens barrel and a solar cell panel which are sequentially arranged along the direction of sunlight propagation; the focusing lens barrel comprises a light-passing pipe (1), a filter (2) and a focusing lens (3); the filter (2) and the focusing lens (3) are both arranged on the light-passing pipe (1) and sequentially arranged along the direction of sunlight propagation; and the solar cell panel is electrically connected to the camera and the positioner at the same time.

9. The positioning and control system of the mobile charging robot according to claim 8, characterized in that: The positioning and control system also includes a lithium battery and a selector. The selector is configured to call the solar panel to be electrically connected to the camera and the locator when the voltage output by the solar panel is not less than a threshold voltage; and call the lithium battery to be electrically connected to the camera and the locator when the voltage output by the solar panel is less than a threshold voltage. The first pin of the selector is electrically connected to the solar panel, the second pin of the selector is electrically connected to the lithium battery, and the third pin of the selector is electrically connected to the camera and the locator at the same time.

10. A method for positioning and controlling a mobile charging robot, characterized in that: The positioning and control system of the mobile charging robot according to any one of claims 1 to 9 comprises the following steps: S1: The user uploads the charging request information containing the location of the electric vehicle to be charged through the collection device; S2: receiving the charging request information through a processing module, and sending a call instruction to the robot body closest to the location of the electric vehicle to be charged; S3: receiving a call instruction sent to the robot body through a body driving device on the robot body closest to the location of the electric vehicle to be charged, and driving the robot body to move from the current position to the location of the electric vehicle to be charged by a dynamic window path planning algorithm according to the received call instruction; S4: calling the charging actuator to charge through the driving device on the robot body closest to the location of the electric vehicle to be charged, and continuously sending a waiting-to-call signal to the processing module after charging is completed to indicate that the robot body is in a waiting-to-call state.

Images