A method for robot motion path planning and a robot

Abstract

The embodiments of the present application disclose a method for robot motion path planning and a robot, which are used to enable the robot to autonomously adjust the motion trajectory according to the environment, thereby improving the action efficiency of the robot. The method of the embodiments of the present application includes: obtaining the current state information of the robot, the position information of all boundary points of the object in the target area, and the global map of the surrounding environment; generating the global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map; obtaining the local map within the preset range of the robot; determining the path target boundary point of the robot according to the global boundary path trajectory and the current position information; calculating the local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary point; controlling the robot to move along the local path trajectory.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of robot control, and particularly to a method for planning a robot motion path and a robot. Background Art

[0002] Compared with traditional wheeled robots and tracked robots, the advantage of legged robots lies in their good obstacle-crossing performance. The multi-degree-of-freedom leg-foot structure of legged robots enables them to cope with some relatively complex terrains. And as a bionic robot of common mammals, the quadruped robot has good application prospects and potential.

[0003] In the prior art, when a speed command is given to a quadruped robot, the robot will walk straight at a certain speed and according to a fixed point. When the robot is in an area with uneven road surfaces such as the foot of a mountain, or in scenarios such as orchards, and is performing the task of spraying pesticides on fruit trees, on the premise of uneven road surfaces and with the obstruction of obstacles such as passers-by, since the robot walks straight according to a fixed point and cannot autonomously adjust its action trajectory according to the uneven ground or obstacles, the action efficiency of the robot will be affected. Summary of the Invention

[0004] The embodiments of the present application provide a method for planning a robot motion path and a robot, which are used to enable the robot to autonomously adjust its motion trajectory according to the environment, thereby improving the action efficiency of the robot.

[0005] The present application provides a method for planning a robot motion path from a first aspect, including:

[0006] Obtain the current state information of the robot, the position information of all boundary points of an object in the target area, and the global map of the surrounding environment, where the current state information includes the current position information and the current orientation information;

[0007] Generate a global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map, where the global boundary path trajectory includes all the boundary points;

[0008] Obtain a local map within the preset range of the robot, where the local map covers at least one of the boundary points;

[0009] Determine the path target boundary point of the robot according to the global boundary path trajectory and the current position information;

[0010] Calculate a local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary point;

[0011] Control the robot to move along the local path trajectory.

[0012] The present application provides a robot from a second aspect, including:

[0013] A first acquisition unit configured to acquire the current state information of the robot, the position information of all boundary points of an object in a target area, and a global map of the surrounding environment, where the current state information includes current position information and current orientation information;

[0014] A first generation unit configured to generate a global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map, where the global boundary path trajectory includes all the boundary points;

[0015] A second acquisition unit configured to acquire a local map within a preset range of the robot, where the local map covers at least one of the boundary points;

[0016] A first determination unit configured to determine a path target boundary point of the robot according to the global boundary path trajectory and the current position information;

[0017] A first calculation unit configured to calculate a local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary point;

[0018] A motion control unit configured to control the robot to move along the local path trajectory.

[0019] As can be seen from the above technical solutions, the embodiments of the present application have the following advantages:

[0020] First, after acquiring the current state information of the robot, the position information of all boundary points of an object in a target area, and a global map of the surrounding environment, a global boundary path trajectory of the object can be generated according to the current position information, the position information of all boundary points of the object, and the global map. After acquiring a local map within a preset range of the robot, a path target boundary point of the robot is further determined according to the global boundary path trajectory and the current position information. Then, according to the obtained local map, the current position information, and in combination with the path target boundary point of the robot, a local path trajectory of the robot is calculated. The present application plans an ideal global boundary path trajectory of the robot by means of generating a boundary path trajectory of the object according to the current state information of the robot and the position information of all boundary points of the object. After determining the path target boundary point through the global boundary path trajectory, a local path trajectory of the robot is calculated according to the local map information, the current position information of the robot, and the path target boundary point. Further, an actual motion path is planned for the robot based on the ideal motion path, so as to enable the robot to autonomously adjust the motion trajectory according to the environment, thereby improving the action efficiency of the robot. Description of the Drawings

[0021] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0022] Figure 1 Schematic diagram of the hardware structure of the multi-legged robot provided by the present application;

[0023] Figure 2 Schematic diagram of the mechanical structure of the multi-legged robot provided by the present application;

[0024] Figure 3 Schematic diagram of the flowchart of an embodiment of the robot motion path planning method provided by the present application;

[0025] Figure 4 Schematic diagram of the global map of the robot motion path planning method provided by the present application;

[0026] Figure 5 Schematic diagram of the global boundary path trajectory of the robot motion path planning method provided by the present application;

[0027] Figure 6 Schematic diagram of the local path trajectory of the robot motion path planning method provided by the present application;

[0028] Figure 7 Schematic diagram of the flowchart of another embodiment of the robot motion path planning method provided by the present application;

[0029] Figure 8 Schematic diagram of the structure of an embodiment of the robot provided by the present application;

[0030] Figure 9 Schematic diagram of the structure of another embodiment of the robot provided by the present application;

[0031] Figure 10 Schematic diagram of the structure of an embodiment of the robot motion path planning device provided by the present application. Detailed implementation manners

[0032] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0033] In the subsequent description, suffixes such as "module", "component", or "unit" used to represent components are only for the convenience of describing the present invention, and they have no specific meaning themselves. Therefore, "module", "component", or "unit" can be used interchangeably.

[0034] Please refer to Figure 1 , Figure 1 , which is a schematic diagram of the hardware structure of the multi-legged robot 100 according to one embodiment of the present invention. In Figure 1 the embodiment shown, the multi-legged robot 100 includes a mechanical unit 101, a communication unit 102, a sensing unit 103, an interface unit 104, a storage unit 105, a control module 110, and a power supply 111. The various components of the multi-legged robot 100 can be connected in any way, including wired or wireless connections, etc. Those skilled in the art can understand that Figure 1 the specific structure of the multi-legged robot 100 shown in

[0035] does not constitute a limitation on the multi-legged robot 100. The multi-legged robot 100 may include more or fewer components than those shown, and some components are not essential components of the multi-legged robot 100 and can be omitted or combined according to needs within the scope of not changing the essence of the invention. Figure 1 The following will specifically introduce each component of the multi-legged robot 100 in conjunction with

[0036] The mechanical unit 101 is the hardware of the multi-legged robot 100. As Figure 1 shown, the mechanical unit 101 may include a drive board 1011, motors 1012, and a mechanical structure 1013. As Figure 2 shown, the mechanical structure 1013 may include a fuselage main body 1014, extendable legs 1015, and feet 1016. In other embodiments, the mechanical structure 1013 may further include an extendable robotic arm, a rotatable head structure, a wagging tail structure, a load-carrying structure, a saddle structure, a camera structure, etc. It should be noted that each component module of the mechanical unit 101 can be one or more, and can be set according to specific circumstances. For example, the number of legs 1015 can be 4, and each leg 1015 can be configured with 3 motors 1012, corresponding to 12 motors 1012.

[0037] The communication unit 102 can be used for signal reception and transmission, and can also communicate with the network and other devices. For example, after receiving instruction information sent by a remote control or other multi-legged robots 100 to move in a specific gait at a specific speed value in a specific direction, it is transmitted to the control module 110 for processing. The communication unit 102 includes modules such as a WiFi module, a 4G module, a 5G module, a Bluetooth module, and an infrared module.

[0038] The sensing unit 103 is used to obtain information data of the environment around the multi-legged robot 100 and monitor the parameter data of various components inside the multi-legged robot 100, and send them to the control module 110. The sensing unit 103 includes a variety of sensors, such as sensors for obtaining surrounding environment information: lidar (for remote object detection, distance determination, and / or speed value determination), millimeter-wave radar (for short-range object detection, distance determination, and / or speed value determination), cameras, infrared cameras, Global Navigation Satellite System (GNSS), etc. Such as sensors for monitoring various components inside the multi-legged robot 100: Inertial Measurement Unit (IMU) (for measuring speed values, acceleration values, and angular velocity values), sole sensors (for monitoring the position of the sole contact point, sole posture, contact force magnitude and direction), temperature sensors (for detecting component temperature). As for other sensors that the multi-legged robot 100 can also be configured with, such as load sensors, touch sensors, motor angle sensors, torque sensors, etc., they will not be elaborated here.

[0039] The interface unit 104 can be used to receive inputs from external devices (such as data information, power, etc.) and transmit the received inputs to one or more components within the multi-legged robot 100, or can be used to output to external devices (such as data information, power, etc.). The interface unit 104 may include a power port, a data port (such as a USB port), a memory card port, a port for connecting a device with an identification module, an audio input / output (I / O) port, a video I / O port, etc.

[0040] The storage unit 105 is used to store software programs and various data. The storage unit 105 may mainly include a program storage area and a data storage area. Among them, the program storage area can store operating system programs, motion control programs, application programs (such as text editors), etc.; the data storage area can store data generated during the use of the multi-legged robot 100 (such as various sensing data obtained by the sensing unit 103, log file data), etc. In addition, the storage unit 105 may include a high-speed random access memory, and may also include a non-volatile memory, such as a disk memory, a flash memory, or other non-volatile solid-state memories.

[0041] The display unit 106 is used to display information input by the user or information provided to the user. The display unit 106 may include a display panel 1061, and the display panel 1061 can be configured in the form of a Liquid Crystal Display (LCD), an Organic Light-Emitting Diode (OLED), etc.

[0042] The input unit 107 can be used to receive input digital or character information. Specifically, the input unit 107 can include a touch panel 1071 and other input devices 1072. The touch panel 1071, also known as a touch screen, can collect the touch operations of users (such as the operations of users using their palms, fingers or suitable accessories on or near the touch panel 1071), and drive the corresponding connection device according to a preset program. The touch panel 1071 can include two parts: a touch detection device 1073 and a touch controller 1074. Among them, the touch detection device 1073 detects the touch orientation of the user, detects the signal brought by the touch operation, and transmits the signal to the touch controller 1074; the touch controller 1074 receives the touch information from the touch detection device 1073, converts it into contact coordinates, and then sends it to the control module 110, and can receive and execute the commands sent by the control module 110. In addition to the touch panel 1071, the input unit 107 can also include other input devices 1072. Specifically, the other input devices 1072 can include, but are not limited to, one or more of a remote control operation handle, etc., and are not specifically defined here.

[0043] Further, the touch panel 1071 can cover the display panel 1061. After the touch panel 1071 detects a touch operation on or near it, it transmits the operation to the control module 110 to determine the type of touch event. Subsequently, the control module 110 provides corresponding visual output on the display panel 1061 according to the type of touch event. Although in Figure 1 , the touch panel 1071 and the display panel 1061 are implemented as two independent components to separately implement the input and output functions, but in some embodiments, the touch panel 1071 and the display panel 1061 can be integrated to implement the input and output functions, which are not specifically defined here.

[0044] The control module 110 is the control center of the multi-legged robot 100. It uses various interfaces and lines to connect all the components of the entire multi-legged robot 100. By running or executing the software programs stored in the storage unit 105, and calling the data stored in the storage unit 105, the multi-legged robot 100 is overall controlled.

[0045] The power supply 111 is used to supply power to each component. The power supply 111 can include a battery and a power control board. The power control board is used to control functions such as battery charging, discharging, and power consumption management. In Figure 1 the shown embodiment, the power supply 111 is electrically connected to the control module 110. In other embodiments, the power supply 111 can also be electrically connected to the sensing unit 103 (such as a camera, radar, speaker, etc.) and the motor 1012 respectively. It should be noted that each component can be connected to different power supplies 111 respectively, or powered by the same power supply 111.

[0046] On the basis of the above embodiments, specifically, in some embodiments, the multi-legged robot 100 can be communicatively connected through a terminal device. When the terminal device communicates with the multi-legged robot 100, the terminal device can send command information to the multi-legged robot 100. The multi-legged robot 100 can receive the command information through the communication unit 102, and when the command information is received, the command information can be transmitted to the control module 110, so that the control module 110 can process and obtain a target speed value according to the command information. The terminal device includes but is not limited to: a mobile phone with an image shooting function, a tablet computer, a server, a personal computer, a wearable intelligent device, and other electrical devices.

[0047] The command information can be determined according to preset conditions. In one embodiment, the multi-legged robot 100 can include a sensing unit 103, and the sensing unit 103 can generate command information according to the current environment where the multi-legged robot 100 is located. The control module 110 can judge whether the current speed value of the multi-legged robot 100 meets the corresponding preset conditions according to the command information. If it meets, the current speed value and the current gait of the multi-legged robot 100 will be maintained for movement; if it does not meet, the target speed value and the corresponding target gait will be determined according to the corresponding preset conditions, so as to control the multi-legged robot 100 to move at the target speed value and the corresponding target gait. The environmental sensors can include temperature sensors, pressure sensors, vision sensors, and sound sensors. The command information can include temperature information, pressure information, image information, and sound information. The communication method between the environmental sensors and the control module 110 can be wired communication or wireless communication. The wireless communication methods include but are not limited to: wireless networks, mobile communication networks (3G, 4G, 5G, etc.), Bluetooth, and infrared.

[0048] The above describes the hardware structure and mechanical structure of the robot provided by the present application. Next, the robot motion path planning method and the functions of the robot provided by the present application will be described.

[0049] In the prior art, when a multi-legged robot receives a speed command, the robot can walk in a straight line at a certain speed and according to a fixed point. However, when the multi-legged robot is in an area with uneven road surfaces or there are dynamic obstacles blocking, it cannot autonomously adjust its movement trajectory according to the uneven ground or these dynamic obstacles, and still walks in a fixed-point straight line. It is difficult to avoid pits, obstacles, etc., which will affect the actual movement speed of the robot and thus affect the movement efficiency of the robot.

[0050] Based on this, the present application provides a robot motion path planning method and a robot, which are used to realize the function of the robot to autonomously adjust the movement trajectory according to the environment, thereby improving the movement efficiency of the robot.

[0051] Please refer to Figure 3 , Figure 3 which provides an embodiment of the robot motion path planning method for this application. For convenience of description, in this embodiment, the robot control system is taken as the execution subject for illustration. The method includes:

[0052] 301. Obtain the current state information of the robot, the position information of all boundary points of the objects in the target area, and the global map of the surrounding environment. The current state information includes the current position information and the current orientation information;

[0053] In the embodiment of this application, in order to better plan the path that the robot will travel, first, it is necessary to know which action orientation the robot is currently in, such as north, south, east, west, left, or right, etc. Then, obtain the environmental conditions of the target area where the robot will act, so as to determine the approximate path trajectory of the robot in the target area based on this information.

[0054] Specifically, when the robot control system receives a user's motion path planning request, it can first obtain the current state information of the robot bound to the robot control system. The current state information includes the current position information and the current orientation information. For example, the acquisition method of the current position information includes, but is not limited to, obtaining the current longitude and latitude of the robot according to the navigation and positioning device set by the robot itself; or setting the target area as a global map with a coordinate system, and determining the coordinate data of the robot in this global map according to the position of the robot in the target area, etc. The current orientation information refers to the direction information where the front of the current robot is located. More specifically, for example: The robot starts from point A and goes to point B. Point A is the starting point and point B is the ending point. If point B is on the left side of point A, then the current orientation of the robot is the left side.

[0055] There are at least two or more boundary points of the object in the target area. The boundary points of the object refer to the points on the boundary around the object for one circle. The number of boundary points of each object can be custom-set or generated by the robot control system for the object, or can be artificial markers placed on the edge of the object as boundary points, etc., which are not limited here. The object in the target area referred to here is the object that the robot needs to act on.

[0056] 302. Generate the global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map;

[0057] As Figure 4 shown, Figure 4It represents a top-down schematic diagram of an orchard scene. In the embodiments of the present application, the target area may refer to the orchard scene area. Then, the objects in the target area are the fruit trees in the orchard. The black dot parts in the figure represent the fruit trees, and the white parts at the edges of the black dots are the edges of the fruit trees. Therefore, the boundary points will be set on the line of the outer edge of the white part, and there are at least two or more boundary points set on the line of the outer edge.

[0058] Determine the path boundary points of each movement according to the preset control logic. The connection of the path boundary points in multiple control cycles forms the global boundary path trajectory of the robot. Specifically, use the current position coordinates of the robot as the starting point of the path trajectory, and use each boundary point of each object as the path boundary point of the robot. Mark these points on the global map and connect them to generate the global boundary path trajectory. The global boundary path trajectory referred to here is the trajectory in an ideal state, that is, the path trajectory without considering the terrain and any obstacles in the target area. The global boundary path trajectory based on the global map can be as Figure 5 shown. Figure 5 is a map containing the global path trajectory generated based on Figure 4 . In Figure 5 , four boundary points are set for each object. Among them, Figure 5 point A is the current position coordinate point of the robot, and line B is the generated global boundary path trajectory, and this global boundary path trajectory includes all boundary points.

[0059] 303. Obtain a local map within the preset range of the robot;

[0060] In the embodiments of the present application, the local map is a local elevation map of the target area, and this local map covers at least one boundary point. For example, the position coordinates of the robot are set as [0, 0], and the coordinates [x0, y0], [x1, y1], [x3, y3], [x4, y4] represent a point on the side of the robot. These points are arranged counterclockwise or clockwise and are respectively a point on the side of the local map. The range area constructed by these points covers at least one boundary point.

[0061] In an embodiment of the present application, after obtaining the local map, based on the motion performance parameters of the robot, the local footprint passable map (local footprint passable map) can be further obtained through the local elevation map. In this way, the local path trajectory of the robot can be determined according to the local map and the corresponding local footprint passable map in the subsequent process. Among them, the elevation mentioned in the embodiment of the present application represents the distance from the geoid, which can be used to represent the height of a point in topographic map measurement, and contour lines can also be obtained from the measured elevation map. The motion performance parameters of the robot mentioned include at least one of the height threshold for crossing steps, the roughness threshold for passing through the ground, the slope threshold for passing through slopes, and the height threshold for passing through suspended objects.

[0062] Regarding the acquisition of the local map, more specifically, the robot control system can set the preset range to a range of 20 m away from the robot. Then, according to information such as laser and perception, the local elevation map of this range is obtained in real time within the range of a point [0, 20], [-20, 0], [0, -20], [20, 0] beside the robot. Compared with the global map, the global map does not show the terrain and topography of the target area and only contains objects; while the local map will accurately and meticulously show the local specific terrain and topography, and in addition to objects, it will also contain dynamic objects existing locally.

[0063] 304. Determine the path target boundary point of the robot according to the global boundary path trajectory and the current position information;

[0064] In an embodiment of the present application, in order to better layout the boundary points that the robot has to experience for each movement, the robot control system can determine the boundary points experienced for each movement according to the distance between the robot and the boundary points. More specifically, as Figure 5 shown, the global boundary path trajectory is B. The robot control system can detect that the next boundary point closest to the position coordinate A based on the global boundary path trajectory B on the global map and the current position coordinate A of the robot is C. Then, this boundary point C is used as the path target boundary point that the robot has to experience next.

[0065] 305. Calculate the local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary point;

[0066] In practical applications, in order to enable the robot to effectively respond to actual situations (such as uneven terrain and the presence of obstacles) during movement, it is necessary to perform regional analysis on the local map of the movement currently executed by the robot based on the generated global boundary path trajectory.

[0067] Specifically, when there are no obstacles or the terrain is flat in the local map, it can be determined that the corresponding path parts of the local path trajectory and the global boundary path trajectory of the robot are the same; when there are obstacles or the terrain is uneven in the local map, as Figure 6 shown, black squares can be used to represent obstacles. When the current position of the robot is A and the determined path target boundary point for the robot is boundary point C, there are obstacles in the global boundary path from point A to point C. To avoid the obstacles, the robot cannot directly follow the global boundary path of the shortest optimal path. The robot control system will substitute the position coordinates of the obstacles in the local map, the current position coordinates of the robot (starting coordinate point), and the path target boundary point (local end coordinate point) into algorithms including but not limited to the A path planning algorithm (A*, A-star algorithm) or the D path planning algorithm (D*, Dynamic A*), etc., to real-time plan the corresponding local 2.5D path, and this local 2.5D path is the local path trajectory of the robot in the corresponding local area.

[0068] 306. Control the robot to move along the local path trajectory.

[0069] In the embodiment of the present application, the robot control system first plans the global path with all boundary points, and then plans the local path including the boundary points. Since it is considered that when the robot moves along the planned path, it needs to avoid obstacles, therefore, whenever the robot updates the path target boundary point once, the robot control system has to analyze and calculate and update the corresponding local path trajectory through step 305 until the robot traverses all boundary points of each object in the target area.

[0070] For example, when the robot control system calculates the local path trajectory of the robot from point C to point D through step 305, it will replace the previous local path trajectory (the local path trajectory of the robot from point A to point C) with this local path trajectory, and send a motion control instruction to the robot, so as to control the robot to move from point C to point D along the newly planned local path trajectory.

[0071] It should be noted that in the embodiment of the present application, the moving gait of the robot is the trot gait, and the motion action is that two legs of the legged robot are on the ground and two legs are in the air. Each leg of the robot has two phases, one is the stance phase (representing on the ground), and the other is the swing phase (representing in the air). To determine whether the robot has passed the path target boundary point, it only needs to determine whether the legs of the robot have completed these two phases at the position of the path target boundary point.

[0072] In the embodiment of the present application, the global boundary path trajectory of the robot in the ideal state is planned by the technical means of generating the boundary path trajectory of the object according to the current state information of the robot and the position information of all boundary points of the object. After determining the path target boundary point through the global boundary path trajectory, the local path trajectory of the robot is calculated according to the local map information, the current position information of the robot, and the path target boundary point by the technical means. Further, an actual motion path is planned for the robot based on the ideal motion path, so that the robot can autonomously adjust the motion trajectory according to the environment, enabling the robot to complete the boundary points considering obstacles, thereby improving the action efficiency of the robot.

[0073] Please refer to Figure 7 , another embodiment of the robot motion path planning method is provided in the present application. For the convenience of description, in this embodiment, the robot control system is taken as the execution subject for illustration. The method includes:

[0074] 401. Obtain the current state information of the robot, the position information of all boundary points of the object in the target area, and the global map of the surrounding environment. The current state information includes the current position information and the current orientation information;

[0075] 402. Generate the global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map;

[0076] In the embodiment of the present application, the current position information of the robot includes the current position coordinates of the robot, and the position information of all boundary points of the object includes the position coordinates of all boundary points of the object. The specific manifestation of generating the global boundary path trajectory may include but is not limited to the following methods.

[0077] For example, based on the current orientation information of the robot, the coordinate point closest to the current position coordinates is determined from the position coordinates of all boundary points of the object as the first coordinate point. The coordinate point referred to here is the coordinate point of the boundary point. The motion direction of the robot is determined according to the current position coordinates and the first coordinate point. After determining the coordinate point closest to the first coordinate point from the position coordinates of all boundary points of the object as the second coordinate point, the first coordinate point is deleted from the position coordinates of all boundary points of the object.

[0078] Determine the coordinate point closest to the second coordinate point from the position coordinates of all boundary points of the object as the third coordinate point. After deleting the second coordinate point, update the third coordinate point to the second coordinate point. Traverse the position coordinates of all boundary points of the object according to the above method, and use the previously determined first coordinate point distribution as the starting coordinate point and the ending coordinate point of the object. Connect the sequentially determined second coordinate points in order and save them to the global map. After traversing all objects in the target area according to the above method, sequentially connect the ending coordinate points of each object to generate a global boundary path trajectory.

[0079] To explain the method of generating a global boundary path trajectory more clearly, the following takes Figure 5 as an example to illustrate an application scenario of this method:

[0080] Suppose the position of the robot is point A, points C, D, F, and G are the boundary points of an object respectively, and point E is one of the boundary points of another object. The coordinate points closest to the position coordinate of point A are point C and point E. Since the current orientation information of the robot is towards the southwest, it is determined that point C corresponding to the southwest orientation is the first coordinate point. Then, the extension direction from point A to point C can be used as the movement direction of the robot: southwest direction. When the robot moves to point C, the coordinate points closest to point C are point F and point D. Since the movement direction of the robot is southwest at this time, the robot control system can determine that the robot performs a counterclockwise movement according to the southwest direction, that is, determine point F as the second coordinate point. After saving point F to the global map, delete point C from the position coordinates of all boundary points of the object. Determine the point G closest to point F from the position coordinates of all boundary points of the object containing point F as the third coordinate point. After deleting the original second coordinate point F, update point G to the new second coordinate point. Continue to execute the above method until all the position coordinates of the boundary points of the object are traversed. Then, use the previously determined first coordinate point C as the starting coordinate point and the ending coordinate point of the corresponding object, connect the sequentially determined second coordinate points in order. After traversing all objects in the target area according to the above method, finally, sequentially connect the ending coordinate points of each object (such as the connection between point C and point E), save them to the global map. Then, the line segments formed by sequentially connecting all points of all objects are the global boundary path trajectory.

[0081] It should be noted here that when the movement direction of the robot is on either the southwest or northwest side, it is determined that the robot moves counterclockwise. When the movement direction of the robot is on either the southeast or northeast side, it is determined that the robot moves clockwise. When the movement direction of the robot is on any of the four sides of southeast, southwest, northeast, or northwest, it can randomly select clockwise / counterclockwise movement. It should be noted that when the robot needs to move from the end coordinate point of one object to the start coordinate point of another object, there is no need to determine whether to move clockwise or counterclockwise based on the movement direction of the robot. The robot can directly move to the start coordinate point of the other object.

[0082] 403. Obtain a local map within the preset range of the robot;

[0083] 404. Determine the path target boundary point of the robot according to the global boundary path trajectory and the current position information;

[0084] In the embodiment of the present application, the preset range is the preset radius. Taking the robot's position as the center and drawing a circle with the preset radius, this circular area is the local map. In this circular area, there is at least one boundary point. It should be noted that the preset range, that is, the preset radius, is determined according to the sensing range of the robot. Therefore, the boundary point on the global boundary path trajectory that is closest to the current position coordinates of the robot on the local map is the path target boundary point that the robot has to go through.

[0085] For example, since the sensing range of the robot is a radius of 20m, the preset range is set to 20m. Then, on the 20m×20m local map, the boundary point on the global boundary path trajectory that is farthest from the current position coordinates (0, 0) of the robot is the path target boundary point that the robot has to go through.

[0086] 405. Construct a local passable map based on the movement performance parameters of the robot and the local map;

[0087] 406. Calculate the local path trajectory of the robot according to the local map, the local passable map, the current position information, and the path target boundary point;

[0088] In the embodiment of the present application, the movement performance parameters may include at least one of the height critical value for crossing steps, the roughness critical value for passing through the ground, the slope critical value for passing through slopes, and the height critical value for passing through suspended objects.

[0089] In the embodiments of the present application, the local map may be a local elevation map. The terrain of the local map is analyzed according to the motion performance parameters to obtain the passable area part of the robot. For example, if it is known from the motion performance parameters that the height critical value for the robot to cross the steps is 20 cm, then the area part in the local map where the step height exceeds 20 cm can be hidden or marked with special symbols to indicate that this area is impassable. After the above processing of the local map, the local passable map of the robot can be constructed. The subsequent calculation of the local path trajectory of the robot is similar to the method described in step 305 above and will not be described here.

[0090] 407. Obtain the current environmental video information and / or the current boundary path information;

[0091] 408. Determine whether the robot is moving around an object according to the current environmental video information and / or the current boundary path information. If so, execute step 409; if not, execute step 410;

[0092] 409. Generate the corresponding first operation instruction and perform the corresponding operation according to the first operation instruction;

[0093] In the embodiments of the present application, the current environmental video information refers to the surrounding environmental video recorded by the camera device carried by the robot itself, and the current boundary path information refers to the path trajectory that the robot has experienced in the global boundary path trajectory. When the robot is performing a task, it can take pictures of the surrounding environment in real time or at a specific time interval.

[0094] The pose information of the robot can be expressed as follows: when the robot is on flat ground, the starting and ending points of the movement of each leg foot end of the robot are on the same horizontal plane; when there are uphill / downhill situations for the robot, the starting and ending points of the movement of each leg foot end of the robot will not be on the same horizontal line. After the robot control system uses algorithms such as A* (A-star algorithm) to plan the corresponding local 2.5D path in real time, the local path tracking speed can be controlled according to the planned 2.5D path, the current pose information of the robot, etc., and at the same time, the current motion state of the robot can be analyzed according to the obtained current environmental video information and the current boundary path information. For example, as Figure 5 shown, the system determines that the current path target boundary point where the robot is located is point F according to the boundary path information, and has passed point C before. Combining the obtained surrounding environmental video, if it is detected that there is a certain object in each video frame during the movement cycle from point C to point F in the surrounding environmental video, and the position or external feature coincidence degree of the object in each video frame is relatively high, it is determined that the robot is moving around a certain object.

[0095] Since the robot is equipped with a robotic arm, when performing a task, while the robot moves along a local path trajectory in the target area, certain triggering conditions can be set so that when the conditions are triggered, the robotic arm can grab equipment or perform corresponding actions for the task executed by the robot for auxiliary operations. For example, if the triggering condition is that the robot moves around an object, then when it is detected that the robot reaches the triggering condition, the control system will further generate a first operation instruction and perform corresponding operations on the object according to the first operation instruction. More specifically, for the task scenario in an orchard, when the staff issues an instruction to the robot through the control system to spray pesticides around a fruit tree, then the robot will be pre-carried with pesticide spraying equipment. The system will use the orchard as the target area for the robot to move, and the fruit tree as the object in the target area. When the system determines that the robot is moving around a certain fruit tree in the target area, it will generate a first operation instruction for pesticide spraying and control the robotic arm to grab the pesticide spraying equipment to spray pesticides on the fruit tree according to this first operation instruction.

[0096] 410. Update the local path trajectory, re-acquire the position information of the robot, and determine whether the robot has reached the path target boundary point based on the position information. If so, execute step 411; if not, execute step 414.

[0097] 411. Determine whether the path target boundary point is the last boundary point in the global boundary path trajectory. If so, execute step 412; if not, execute step 413.

[0098] 412. Control the robot to stop moving.

[0099] 413. Based on the global boundary path trajectory and combined with the position information, determine the boundary point in the global boundary path trajectory that is closest to the current position of the robot as the next path target boundary point of the robot.

[0100] 414. Control the robot to keep moving along the local path trajectory.

[0101] In the embodiments of the present application, as the robot continuously moves along the local path trajectory, the robot control system can determine the current motion state of the robot by re-acquiring the position information of the robot, and update the next path target boundary point that the robot will experience according to this motion state until the robot reaches the last boundary point of the global path trajectory in the target area. Specifically, as Figure 5As shown in the figure, assume that the robot has moved from point A to point C, and point C is determined as the path target boundary point. However, it is obvious from the global map or the local map containing point C that point C is not the last boundary point in the global boundary path trajectory. According to the current movement direction of the robot, it can be determined that the point F closest to the current position of the robot is the next path target boundary point of the robot. Assume that the robot's position is between point C and point E, then it can be determined that the robot has not reached the path target boundary point, and the robot is continuously controlled to move along the local path trajectory until it reaches point E.

[0102] In the embodiment of the present application, the robot control system can set certain trigger conditions for the robot according to different task scenarios, so that while the robot moves along the planned global boundary path trajectory, the built-in robotic arm can also, when the conditions are triggered, grab devices or perform corresponding actions for auxiliary operations according to the tasks performed by the robot, and finally complete the tasks, effectively improving the working efficiency of the robot. The movement direction of the robot can be determined according to the relevant information of the robot and all boundary points of the object, and further, all boundary points of the object can be sorted in order according to the movement direction and the distance between the robot and the relevant boundary points. Finally, these boundary points are sequentially connected to generate the global boundary path trajectory, avoiding the problem of the robot taking repeated routes. It can also determine the boundary point in the global boundary path trajectory that is closest to the current position of the robot according to the position information of the robot, and this boundary point is used as the next path target boundary point of the robot, thereby updating the local trajectory path, realizing the judgment and update of the current local trajectory path of the robot.

[0103] Please refer to Figure 8 , Figure 8 which is an embodiment of the robot provided by the embodiment of the present application, including:

[0104] The first acquisition unit 501 is used to acquire the current state information of the robot, the position information of all boundary points of the object in the target area, and the global map of the surrounding environment. The current state information includes the current position information and the current orientation information;

[0105] The first generation unit 502 is used to generate the global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map. The global boundary path trajectory includes all boundary points;

[0106] The second acquisition unit 503 is used to acquire the local map within the preset range of the robot. The local map covers at least one boundary point;

[0107] The first determination unit 504 is used to determine the path target boundary point of the robot according to the global boundary path trajectory and the current position information;

[0108] The first calculation unit 505 is configured to calculate the local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary points.

[0109] The motion control unit 506 is configured to control the robot to move along the local path trajectory.

[0110] In the embodiment of the present application, when the first acquisition unit 501 acquires the current state information of the robot, the position information of all boundary points of the object in the target area, and the global map of the surrounding environment, the first generation unit 502 generates the global boundary path trajectory of the object according to the information acquired by the first acquisition unit 501. Then, the first determination unit 504 is configured to determine the path target boundary points, and the first calculation unit 505 calculates the local path trajectory of the robot according to the current position information acquired by the first acquisition unit 501, the local map acquired by the second acquisition unit 503, and in combination with the path target boundary points determined by the first determination unit 504. Finally, the motion control unit 506 controls the robot to move along the local path trajectory calculated by the first calculation unit 505, improving the action efficiency of the robot.

[0111] Please refer to Figure 9 , Figure 9 which is another embodiment of the robot provided by the embodiment of the present application, and includes:

[0112] The first acquisition unit 601 is configured to acquire the current state information of the robot, the position information of all boundary points of the object in the target area, and the global map of the surrounding environment, where the current state information includes the current position information and the current orientation information.

[0113] The first generation unit 602 is configured to generate the global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map, and the global boundary path trajectory includes all boundary points.

[0114] The second acquisition unit 603 is configured to acquire the local map within the preset range of the robot, and the local map covers at least one boundary point.

[0115] The first determination unit 604 is configured to determine the path target boundary points of the robot according to the global boundary path trajectory and the current position information.

[0116] The first calculation unit 605 is configured to calculate the local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary points.

[0117] The third acquisition unit 606 is configured to acquire the current environment video information and / or the current boundary path information.

[0118] The first determination unit 607 is configured to determine whether the robot is moving around an object according to the current environmental video information and / or the current boundary path information;

[0119] The first execution unit 608 is configured to, when the first determination unit 607 determines according to the current environmental video information and / or the current boundary path information that the robot is moving around an object, generate a corresponding first operation instruction and execute a corresponding operation according to the first operation instruction;

[0120] The motion control unit 609 is configured to control the robot to move along a local path trajectory.

[0121] In the embodiment of the present application, the current position information includes the current position coordinates of the robot, and the position information of all boundary points of the object includes the position coordinates of all boundary points of the object.

[0122] In the embodiment of the present application, the first generation unit 602 is specifically configured to determine, based on the current orientation information of the robot, the coordinate point closest to the current position coordinates from the position coordinates of all boundary points of the object as the first coordinate point, determine the motion direction of the robot according to the current position coordinates and the first coordinate point, determine the coordinate point closest to the first coordinate point from the position coordinates of all boundary points of the object as the second coordinate point according to the motion direction, and delete the first coordinate point from the position coordinates of all boundary points of the object;

[0123] The first generation unit 602 is further specifically configured to determine the coordinate point closest to the second coordinate point from the position coordinates of all boundary points of the object as the third coordinate point, delete the second coordinate point from the position coordinates of all boundary points of the object, update the third coordinate point to the second coordinate point, traverse the position coordinates of all boundary points of the object according to the above method, use the first coordinate point as the starting coordinate point and the ending coordinate point of the object, connect the sequentially determined second coordinate points in sequence and save them to the global map, and after traversing all objects in the target area according to the above method, connect the ending coordinate points of each object in sequence to generate a global boundary path trajectory.

[0124] In the embodiment of the present application, the first calculation unit 605 includes:

[0125] The map construction module 6051 is configured to construct a local passable map based on the motion performance parameters of the robot and the local map;

[0126] The local path trajectory calculation module 6052 is configured to calculate the local path trajectory of the robot according to the local map, the local passable map, the current position information, and the path target boundary point.

[0127] In the embodiment of the present application, the motion control unit 609 includes:

[0128] The first processing module 6091 is used to update the local path trajectory, re-acquire the position information of the robot, and determine whether the robot reaches the path target boundary point according to the position information;

[0129] The second judgment module 6092 is used to judge whether the path target boundary point is the last boundary point in the global boundary path trajectory when the first processing module 6091 determines that the robot reaches the path target boundary point according to the position information;

[0130] The second execution module 6093 is used to control the robot to stop moving when the second judgment module 6092 determines that the path target boundary point is the last boundary point in the global boundary path trajectory;

[0131] The third execution module 6094 is used to determine the boundary point closest to the current position of the robot in the global boundary path trajectory as the next path target boundary point of the robot according to the global boundary path trajectory and in combination with the position information when the second judgment module 6092 determines that the path target boundary point is not the last boundary point in the global boundary path trajectory;

[0132] The fourth execution module 6095 is used to control the robot to move along the local path trajectory when the first processing module 6091 determines that the robot does not reach the path target boundary point according to the position information.

[0133] Please refer to Figure 10 , Figure 10 which provides an embodiment of a robot motion planning device. The robot motion planning device includes:

[0134] A processor 701, a memory 702, an input / output unit 703, and a bus 704;

[0135] The processor 701 is connected to the memory 702, the input / output unit 703, and the bus 704;

[0136] The processor 701 specifically performs the following operations:

[0137] Obtain the current state information of the robot, the position information of all boundary points of the object in the target area, and the global map of the surrounding environment. The current state information includes the current position information and the current orientation information;

[0138] Generate the global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map. The global boundary path trajectory includes all boundary points;

[0139] Obtain the local map within the preset range of the robot. The local map covers at least one boundary point;

[0140] Determine the path target boundary point of the robot according to the global boundary path trajectory and the current position information;

[0141] According to the local map and the current position information, combine the path target boundary point to calculate the local path trajectory of the robot;

[0142] Control the robot to move along the local path trajectory.

[0143] In this embodiment, the function of the processor 701 corresponds to the steps in the foregoing Figure 3 、 Figure 7 illustrated embodiments and will not be elaborated here.

[0144] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated here.

[0145] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be in electrical, mechanical, or other forms.

[0146] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0147] In addition, the functional units in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0148] When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, read-only memory), random access memories (RAM, random access memory), magnetic disks, or optical discs that can store program codes.

Claims

1. A method for robot motion path planning, characterized in that, Including: Obtain the current state information of the robot, the position information of all boundary points of the object in the target area, and the global map of the surrounding environment, where the current state information includes the current position information and the current orientation information; Generate the global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map, where the global boundary path trajectory includes all the boundary points; Obtain the local map within the preset range of the robot, where the local map covers at least one of the boundary points; Determine the path target boundary point of the robot according to the global boundary path trajectory and the current position information; Calculate the local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary point; Control the robot to move along the local path trajectory; The current position information includes the current position coordinates of the robot, and the position information of all boundary points of the object includes the position coordinates of all boundary points of the object; The generating the global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map specifically includes: S1. Based on the current orientation information of the robot, determine the coordinate point closest to the current position coordinates among the position coordinates of all boundary points of the object as the first coordinate point; S2. Determine the movement direction of the robot according to the current position coordinates and the first coordinate point; S3. Determine the coordinate point closest to the first coordinate point among the position coordinates of all boundary points of the object as the second coordinate point according to the movement direction, and delete the first coordinate point from the position coordinates of all boundary points of the object; S4. Determine the coordinate point closest to the second coordinate point among the position coordinates of all boundary points of the object as the third coordinate point; S5. Delete the second coordinate point from the position coordinates of all boundary points of the object, and update the third coordinate point as the second coordinate point; S6. Traverse the position coordinates of all boundary points of the object according to steps S4 to S5, use the first coordinate point as the starting coordinate point and the ending coordinate point of the object, and connect the sequentially determined second coordinate points in sequence and save them to the global map; S7. After traversing all the objects in the target area according to steps S1 to S6, connect the ending coordinate points of each object in sequence to generate the global boundary path trajectory.

2. The robot motion path planning method according to claim 1, wherein Calculating the local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary point includes: Construct a local passable map based on the motion performance parameters of the robot and the local map; Calculate the local path trajectory of the robot according to the local map, the local passable map, the current position information, and the path target boundary point.

3. The robot motion path planning method according to any one of claims 1 to 2, characterized in that, After calculating the local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary point, the robot motion path planning method further includes: Obtain the current environment video information and / or the current boundary path information; Judge whether the robot is moving around the object according to the current environment video information and / or the current boundary path information; If so, generate a corresponding first operation instruction and perform a corresponding operation according to the first operation instruction.

4. The robot motion path planning method according to claim 1, wherein After controlling the robot to move along the local path trajectory, the robot motion path planning method further includes: Update the local path trajectory, re-obtain the position information of the robot, and judge whether the robot reaches the path target boundary point according to the position information; When it is determined according to the position information that the robot reaches the path target boundary point, judge whether the path target boundary point is the last boundary point in the global boundary path trajectory. If so, control the robot to stop moving; If not, determine the boundary point in the global boundary path trajectory that is closest to the current position of the robot as the next path target boundary point of the robot according to the global boundary path trajectory and the position information; When it is determined according to the position information that the robot does not reach the path target boundary point, control the robot to keep moving along the local path trajectory.

5. A robot, characterized in that, Comprising: A first acquisition unit, configured to acquire the current state information of the robot, the position information of all boundary points of the object in the target area, and the global map of the surrounding environment, where the current state information includes the current position information and the current orientation information; A first generation unit, configured to generate the global boundary path trajectory of the object according to the current position information, the position information of all boundary points of the object, and the global map, where the global boundary path trajectory includes all the boundary points; A second acquisition unit, configured to acquire the local map within the preset range of the robot, where the local map covers at least one of the boundary points; A first determination unit, configured to determine the path target boundary point of the robot according to the global boundary path trajectory and the current position information; A first calculation unit, configured to calculate the local path trajectory of the robot according to the local map, the current position information, and in combination with the path target boundary point; A motion control unit, configured to control the robot to move along the local path trajectory; The current position information includes the current position coordinates of the robot, and the position information of all boundary points of the object includes the position coordinates of all boundary points of the object; The first generation unit is specifically configured to: S1, determine, based on the current orientation information of the robot, the coordinate point closest to the current position coordinates from the position coordinates of all boundary points of the object as the first coordinate point; S2, determine the movement direction of the robot according to the current position coordinates and the first coordinate point; S3, determine, according to the movement direction, the coordinate point closest to the first coordinate point from the position coordinates of all boundary points of the object as the second coordinate point, and delete the first coordinate point from the position coordinates of all boundary points of the object; The first generation unit is specifically further configured to: S4. Determine the coordinate point closest to the second coordinate point from the position coordinates of all the boundary points of the object as the third coordinate point; S5. Delete the second coordinate point from the position coordinates of all the boundary points of the object, and update the third coordinate point as the second coordinate point; S6. Traverse the position coordinates of all the boundary points of the object according to steps S4 to S5. Using the first coordinate point as the starting coordinate point and the ending coordinate point of the object, connect the successively determined second coordinate points in sequence and save them to the global map; S7. After traversing all the objects in the target area according to steps S1 to S6, connect the ending coordinate points of each object in sequence to generate a global boundary path trajectory.

6. The robot according to claim 5, wherein, The first calculation unit includes: A map construction module, configured to construct a local passable map based on the motion performance parameters of the robot and the local map; A local path trajectory calculation module, configured to calculate the local path trajectory of the robot according to the local map, the local passable map, the current position information, and the path target boundary point.

7. The robot according to any one of claims 5 to 6, characterized in that, The robot further includes: A third acquisition unit, configured to acquire current environment video information and / or current boundary path information; A first judgment unit, configured to judge whether the robot is moving around the object according to the current environment video information and / or the current boundary path information; A first execution unit, configured to generate a corresponding first operation instruction when the first judgment unit determines according to the current environment video information and / or the current boundary path information that the robot is moving around the object, and execute corresponding operations according to the first operation instruction.

8. The robot according to claim 5, characterized in that, The motion control unit includes: A first processing module, configured to update the local path trajectory, re-acquire the position information of the robot, and judge whether the robot has reached the path target boundary point according to the position information; A second judgment module, configured to judge whether the path target boundary point is the last boundary point in the global boundary path trajectory when the first processing module determines according to the position information that the robot has reached the path target boundary point; A second execution module, configured to control the robot to stop moving when the second judgment module determines that the path target boundary point is the last boundary point in the global boundary path trajectory; A third execution module, configured to determine the boundary point closest to the current position of the robot in the global boundary path trajectory as the next path target boundary point of the robot according to the global boundary path trajectory and in combination with the position information when the second judgment module determines that the path target boundary point is not the last boundary point in the global boundary path trajectory; A fourth execution module, configured to control the robot to move along the local path trajectory when the first processing module determines according to the position information that the robot has not reached the path target boundary point.

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