CN117629219A - Charging positioning guiding method and automatic charging robot - Google Patents

Abstract

The application relates to a charging positioning guiding method and an automatic charging robot. The method comprises the following steps: acquiring environment information, and generating a terrain evaluation value according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot; acquiring a footable point of the robot according to the terrain evaluation value and the reachable range of the robot; and generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence, and planning the motion track of the robot along the navigation path. The method can realize quick charge.

Description

Charging positioning guiding method and automatic charging robot

Technical Field

The application relates to the technical field of robot charging, in particular to a charging positioning guiding method and an automatic charging robot.

Background

With the development of mobile robots, the charging problem of the robots is also attracting attention while focusing on perceived positioning, path planning and autonomous obstacle avoidance. More and more robot products are provided with an automatic recharging function, namely, a function that when a robot completes a task or the battery power is about to run out, the robot automatically returns to a designated charging station or charger for charging.

The existing automatic charging implementation scheme mainly comprises a remote infrared light guiding scheme, a visual tracking service scheme and a grid map-based navigation and obstacle avoidance scheme. Most of the current mainstream methods for short-range docking are to place special shapes or color marks easily recognized by sensors above or around the charging posts to complete the process of recognizing and accurately docking the charging posts. Many automatic charging systems incorporate more than two types of sensors to implement an automatic charging technique.

However, the conventional guiding method is mainly implemented by various sensors configured on the robot, that is, the obstacle avoidance operation is performed by collecting the sensors and then judging by using information transmission, so that the robot cannot be guided most quickly, and quick charging cannot be performed.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a charge positioning guidance method and an automatic charging robot capable of achieving quick charging.

In a first aspect, the present application provides a charging positioning guiding method, including:

acquiring environment information, and generating a terrain evaluation value according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot;

acquiring a footable point of the robot according to the terrain evaluation value and the reachable range of the robot;

and generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence, and planning the motion track of the robot along the navigation path.

In one embodiment, obtaining environmental information, generating a terrain evaluation value from the environmental information includes:

collecting the terrain height and gradient of each collecting point in the area between the current position of the robot and the charging preset position;

acquiring the topography height of the acquisition point according to the topography height and the interpolation function; the interpolation function is a function describing the average height of the acquisition points;

and obtaining terrain evaluation values corresponding to the acquisition points according to the terrain height and the gradient.

In one embodiment, obtaining the footable point of the robot according to the terrain evaluation value and the reach of the robot includes:

judging whether each acquisition point is reachable by the robot according to the terrain evaluation value and the reachable range of the robot, and if so, judging that the acquisition point is a footable point;

the method further comprises the steps of:

evaluating the footable points according to the current position of the robot, the Euclidean distance of the footable points and the reachable range of the robot, and obtaining corresponding evaluation values of the footable points; the evaluation value is used for representing the goodness of the footable point.

In one embodiment, generating a continuous sequence of foothold from the footable points includes:

determining a current foot drop point according to the current position of the robot, and selecting a next foot drop point corresponding to the current foot drop point from the foot drop points according to the current foot drop point; iteratively selecting a foothold until the foothold reaches a charging preset position;

and generating a sequence of foothold points according to the selected order of the foothold points.

In one embodiment, performing stability evaluation on the sequence of foothold points, and planning a motion track of the robot along the navigation path includes:

judging whether the robot can keep balance under a specific motion condition according to a support domain generated by the foot drop point and a stability criterion;

if not, the sequence of the foothold points is adjusted until the robot keeps balance at each foothold point, and the motion trail is obtained.

In one embodiment, the method further comprises:

after the robot reaches a charging preset position along a motion track, entering a preset charging state position and entering a charging state;

and judging that the charging state is valid, and if the charging state is invalid, adjusting the posture of the robot until the charging state becomes valid.

In a second aspect, the present application provides an automatic charging robot

Comprising the following steps:

the environment sensing module is used for acquiring environment information and generating a terrain evaluation value according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot;

the foot-drop point selection module is used for acquiring foot-drop points of the robot according to the terrain evaluation value and the reachable range of the robot;

and the motion track planning module is used for generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence and planning the motion track of the robot along the navigation path.

In a third aspect, the present application provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:

acquiring environment information, and generating a terrain evaluation value according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot;

acquiring a footable point of the robot according to the terrain evaluation value and the reachable range of the robot;

and generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence, and planning the motion track of the robot along the navigation path.

In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:

acquiring environment information, and generating a terrain evaluation value according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot;

acquiring a footable point of the robot according to the terrain evaluation value and the reachable range of the robot;

and generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence, and planning the motion track of the robot along the navigation path.

In a fifth aspect, the present application provides a computer program product comprising a computer program which, when executed by a processor, performs the steps of:

acquiring environment information, and generating a terrain evaluation value according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot;

acquiring a footable point of the robot according to the terrain evaluation value and the reachable range of the robot;

and generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence, and planning the motion track of the robot along the navigation path.

According to the charging positioning guiding method and the automatic charging robot, environment information is acquired, and a terrain evaluation value is generated according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot; acquiring a footable point of the robot according to the terrain evaluation value and the reachable range of the robot; and generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence, and planning the motion track of the robot along the navigation path. According to the method and the device, the robot can be rapidly assisted in selecting the optimal motion track by planning the foothold point, compared with a traditional scheme of judging and planning obstacle avoidance operation based on data acquired and transmitted by the sensor, the method and the device greatly reduce the time cost of carrying out real-time information transmission and judgment planning in the moving process of the robot, so that the speed of the robot reaching a charging position is accelerated, and the charging is faster.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person having ordinary skill in the art.

FIG. 1 is an application environment diagram of a charge location guidance method in one embodiment;

FIG. 2 is a flow chart of a charge positioning and guiding method in one embodiment;

FIG. 3 is a flow chart of a charge positioning and guiding method in one embodiment;

FIG. 4 is a block diagram of the architecture of an environmental awareness system in one embodiment;

FIG. 5 is a block diagram of an automated charging robot in one embodiment;

fig. 6 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The charging positioning guiding method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. The terminal 102 may be, but is not limited to, a robot of various types, such as a sweeping robot, a logistics robot, a patrol robot, etc. The server 104 may be implemented as a stand-alone server or as a server cluster of multiple servers.

In an exemplary embodiment, as shown in fig. 2, a charging location guidance method is provided, which is illustrated by taking an example that the method is applied to the terminal 102 in fig. 1, and includes the following steps 202 to 206.

Wherein:

step 202, acquiring environment information, and generating a terrain evaluation value according to the environment information; the environment information includes terrain information of a navigation path of the robot from the current position to the charging preset position.

Firstly, navigation map building is carried out, a navigation path from the current position to the charging preset position is planned, the navigation path can be planned based on environment information acquired by the robot, and the navigation path can be planned based on a specific environment stored in a memory of the robot.

The environmental information is acquired by using a sightseeing perception technology. The environment sensing technology is to acquire surrounding environment information by using a sensor, computer vision and signal processing, identify, analyze and process the surrounding environment information, firstly acquire the environment information by using a sensing device, convert the environment information into a digital signal, and then analyze the digital signal by using information processing to finally acquire the environment information. The environment sensing technology mainly comprises physical sensing, visual sensing, sound sensing, position sensing and the like, and can realize the omnibearing monitoring and analysis of the environment.

As a preferred solution, the environmental information may be visualized, so that the robot operator may more intuitively perceive the environmental features contained in the environmental information.

The environment information can comprise terrain information on the navigation path, and can further comprise information such as roadblocks, road surface guidance indication marks and the like, so that a reliable navigation path can be planned based on the environment information when navigation is performed.

The terrain evaluation value is a quantitative evaluation of whether the terrain is suitable for the same line, and the corresponding terrain evaluation value is different for the terrain with different rugged degrees; for terrains of different grades, the corresponding terrain assessment values are also different.

And 204, acquiring the footable point of the robot according to the terrain evaluation value and the reachable range of the robot.

The robot's footable point, as the name implies, is the location that the robot can reach. For a biped, tripodal, quadruped or even multipedal robot, the movement of each step of the robot is limited in scope by its shape, step size and other factors. In addition, there are also topographical factors that can affect the movement of the robot, such as a steep grade of terrain, where the robot cannot roll over, and where the partial terrain is not suitable for selection as a footable point for the robot. As another example, there is a pit in the ground that is not sufficiently stepped by the robot and the robot stepping into the pit may damage or sink, and the area near the pit is not suitable for the robot to select as a footable point.

And selecting a foothold point in the vicinity of the navigation path according to the terrain evaluation value and the reachable range of the robot. The area near the navigation path can be enlarged appropriately according to the requirement, and the robot can be adjusted in a self-adaptive manner according to the actual condition of the area near the navigation path.

And 206, generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence, and planning the motion track of the robot along the navigation path.

The embodiment aims at planning of the foot drop point of the robot, so that the motion trail of the robot is actually the motion trail of the mechanical leg of the multi-legged robot. The foot drop point sequence refers to a set of foot drop points with a sequence on the mechanical leg of the robot.

Based on the foot drop point sequence, whether each foot drop point can be kept stable or not when the robot moves along the foot drop point sequence is judged, and the robot can smoothly move on a navigation path only when each step is kept stable. If the robot cannot be stabilized at a certain foothold point, the working task of the robot can be influenced, and the robot can be damaged, so that a large amount of economic loss is caused.

Under the condition of simulation calculation, the robot can stably reach the charging preset position under the guidance of the foothold sequence, and then the motion track of autonomous charging of the robot can be generated according to the foothold sequence, so that the automatic recharging positioning and guiding of the robot are realized.

According to the charging positioning guide method, the environment information is acquired, and the terrain evaluation value is generated according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot; acquiring a footable point of the robot according to the terrain evaluation value and the reachable range of the robot; and generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence, and planning the motion track of the robot along the navigation path. According to the method and the device, the robot can be rapidly assisted in selecting the optimal motion track by planning the foothold point, compared with a traditional scheme of judging and planning obstacle avoidance operation based on data acquired and transmitted by the sensor, the method and the device greatly reduce the time cost of carrying out real-time information transmission and judgment planning in the moving process of the robot, so that the speed of the robot reaching a charging position is accelerated, and the charging is faster.

In one exemplary embodiment, step 202 includes: collecting the terrain height and gradient of each collecting point in the area between the current position of the robot and the charging preset position; acquiring the topography height of the acquisition point according to the topography height and the interpolation function; the interpolation function is a function describing the average height of the acquisition points; and obtaining terrain evaluation values corresponding to the acquisition points according to the terrain height and the gradient.

The terrain information includes terrain elevation and grade. Terrain elevation refers to the vertical distance above or below a reference plane, typically the elevation relative to the mean sea level. Slope refers to the degree of elevation or descent of a terrain, and generally refers to the angle of inclination of the ground, also referred to as the slope angle.

In this embodiment, the acquisition points are uniformly distributed, and the topographic information is acquired according to a preset acquisition granularity.

The calculation formula of the terrain evaluation value is as follows:

f(x,y)＝H(x,y)·K；

wherein x and y respectively represent the horizontal coordinates of the acquisition points in the geographic coordinate system; f (x, y) is a terrain evaluation value; h (x, y) is the relief height; k represents the degree of inclination.

The expression formula of H (x, y) is: h (x, y) =z (x, y) -f' (x, y); wherein Z (x, y) represents the terrain height of the acquisition point (x, y), f' (x, y) represents the interpolation function value of the acquisition point (x, y), and the interpolation function is a function for describing the average height of the terrain at the acquisition point (x, y), and is generally obtained by adopting a triangle grid interpolation method or a quadtree interpolation method and the like.

K is expressed as: k=tan α; where α represents a gradient.

Discrete terrain elevation data can be converted to a continuous function by interpolation functions to calculate the elevation of the acquisition point relative to the surrounding terrain.

The function f (x, y) maps (x, y) to an elevation value, which is the terrain evaluation value. The terrain evaluation value is widely applied to the fields of terrain analysis, landform classification, hydrologic simulation and the like in a geographic information system (GIS, geographic Information System), and by analyzing the terrain evaluation value, the information of the height, slope direction and the like of the terrain can be determined, and the landform classification can be performed according to the information. The present embodiment can evaluate the suitability of each acquisition point as a footable point by the terrain evaluation value.

In an optimization scheme, the ground row evaluation value is drawn into a terrain evaluation chart so as to reflect the terrain condition more intuitively and reflect the selection basis of the footable point more intuitively.

In an exemplary embodiment, step 204 includes: and judging whether each acquisition point is reachable by the robot according to the terrain evaluation value and the reachable range of the robot, and if so, judging that the acquisition point is a footable point.

And judging whether the acquisition point is reachable by the robot according to the terrain evaluation value and the reachable range of the robot, so that the acquisition point is screened, the footfalls point is selected, and the calculation workload of the subsequent determination of the actual footfalls point is reduced.

In an exemplary embodiment, the method further comprises: evaluating the footable points according to the current position of the robot, the Euclidean distance of the footable points and the reachable range of the robot, and obtaining corresponding evaluation values of the footable points; the evaluation value is used for representing the goodness of the footable point.

The landing point evaluation algorithm is an algorithm for determining an optimal landing point, and is commonly used in navigation and control of robots, unmanned aerial vehicles or other autonomous systems, and the algorithm evaluates possible landing points based on sensor data, an environment model and dynamic constraints and determines the optimal landing point.

The foot drop evaluation algorithm can evaluate the advantages and disadvantages of the foot drop of the robot at different positions by calculating parameters such as the length, the speed, the direction and the like of a travel path of the robot, and the algorithm uses various mathematical models and algorithms such as Euclidean distance, manhattan distance, A-type algorithm and the like, and is based on the travel path of the robot and the time required for reaching a target point, so that the optimal foot drop is obtained.

The expression of the footfall point evaluation algorithm in this embodiment is:

∫(x,y)＝w1*d(x,y)+w2*(1-exp(-α*d(x,y)))+w3*g(x,y)；

wherein, the ≡ (x, y) represents an evaluation function, and x and y represent coordinates of a robot foot drop point; d (x, y) represents the Euclidean distance between the current position of the robot and the landing point; exp (- α x d (x, y)) represents an exponential function, where α is an adjustment parameter; g (x, y) is a limiting function for defining a feasible range of the foot drop point of the robot, and the weight coefficients w1, w2 and w3 respectively represent a distance weight, a reachability weight and a constraint weight, wherein the distance weight is used for measuring the importance of the distance of the robot to the foot drop point, the reachability weight is used for measuring the importance of the accessibility of the foot drop point, and the constraint weight is used for measuring the importance of the feasible range of the foot drop point.

In one exemplary embodiment, in step 206, generating a continuous sequence of foothold from the footable points includes: determining a current foot drop point according to the current position of the robot, and selecting a next foot drop point corresponding to the current foot drop point from the foot drop points according to the current foot drop point; iteratively selecting a foothold until the foothold reaches a charging preset position; and generating a sequence of foothold points according to the selected order of the foothold points.

And (3) planning a foot drop point sequence, namely, considering the motion accessibility and the terrain information of the robot according to the generated navigation path, obtaining foot drop points in a swinging foot reachable area in the terrain, and finally, determining continuous foot drop points of the robot according to a foot drop point evaluation algorithm. The successive footfalls form a sequence of footfalls.

In an exemplary embodiment, in step 206, performing stability evaluation on the sequence of foothold points, planning a motion trajectory of the robot along the navigation path includes: judging whether the robot can keep balance under a specific motion condition according to a support domain generated by the foot drop point and a stability criterion; if not, the sequence of the foothold points is adjusted until the robot keeps balance at each foothold point, and the motion trail is obtained.

The stability criterion is based on Newton mechanics principle, and whether the robot can keep balance under a specific motion condition is judged by analyzing inertia force, gravity and contact force under the motion state of the robot.

The supporting domain generated by the falling point refers to that the swinging foot falls on the falling point in the alternating process of the supporting foot and the swinging foot, so that the robot can keep stable supporting force of the body, and the combination of the supporting force is the supporting domain.

If the robot can keep balance at a certain foothold, the foothold before and after the foothold in the sequence of footholds is reserved. If the robot cannot keep stable, the foothold is reselected forward according to the sequence of foothold. If the foothold of the previous position is reselected, but a proper foothold which can enable the foothold of the previous position and the current foothold to simultaneously meet the stability criterion cannot be deduced and found, the foothold is reselected forwards. All the foothold points from the current position to the charging preset position of the robot can be kept balanced. At this time, the motion trail can be obtained according to the generated foothold sequence.

According to the track planning method, a series of smooth tracks are generated according to the support domain generated by the foothold points and the stability criterion, so that the gravity center of the robot smoothly moves in the stable area along the planned tracks, and the stability of the quadruped robot in the walking process is ensured.

In an exemplary embodiment, the method further comprises: after the robot reaches a charging preset position along a motion track, entering a preset charging state position and entering a charging state; and judging that the charging state is valid, and if the charging state is invalid, adjusting the posture of the robot until the charging state becomes valid.

The charging preset position and the charging state position are preset positions, wherein the charging preset position is arranged at the position of 0.3 to 0.7 meter right in front of the charging pile. After entering the charging preset position, the robot needs to reduce the speed to slowly enter the charging state position from the charging preset position.

The interface of robot automatic charging is generally contact joint, and the robot adjusts the gesture after moving to the charge state position and carries out the contact joint that charges to when entering charge state, whether charge is effective judgement is carried out. If the charging state is effective, the posture is kept for charging, and the charging is waited for completion; if the charging contact is invalid, the posture is adjusted, the engagement of the charging contact is ensured, and after the charging is judged to be valid, the charging is started and the completion of the charging is waited.

In this embodiment, the posture adjustment includes a body height and posture adaptive adjustment plan and swing leg trajectory plan. The self-adaptive adjustment planning of the body height and the gesture is to estimate the height and the gradient of the terrain through an environment sensing system and combining with the kinematics of the quadruped robot, and control the change of the height of the quadruped robot and the self-adaptive terrain height and the gradient of the gesture. The body height and posture are adjusted by sensing the height, obstacle and running gradient information of the surrounding environment through the sensors of the four-legged robot, and then adjusting the body height and posture through corresponding driving according to the information.

The swing leg track planning is to obtain the topographic information of the swing leg between the foot drop point and the foot lifting point through the environment sensing system, plan the swing leg track so as to avoid the collision between the leg and the topographic information in the swing process, and when planning the sole track, the acceleration and the speed of the foot are zero when the foot is lifted and dropped so as to ensure the continuity of the motion and avoid great impact on the quadruped robot.

Through whether the effective judgement of charging, can ensure effectual charging.

In one embodiment, as shown in fig. 3, the charge positioning guide method includes:

step 302, a navigation path from the current location to the charging preset location is planned.

And step 304, acquiring environment information on the navigation path, and generating a terrain evaluation value according to the environment information.

And 306, acquiring the footable points of the robot according to the terrain evaluation value and the reachable range of the robot, and generating a continuous footable point sequence according to the footable points.

Step 308, performing stability evaluation on the foothold sequence; if the foot drop point is stable, recording that the foot drop point is reachable; if not, changing the landing point.

Step 310, obtaining a final foothold sequence and generating a motion trail.

In one embodiment, as shown in fig. 4, the robot's environmental awareness system includes a time synchronization board, a Velodyne 16-line radar, an IMU (Inertial Measurement Unit ) inertial element, an intel realsense camera, and a NUC (Next Unit of Computing, calculate next unit) computing platform. The time synchronization board is used for providing synchronization signals of the Velodyne16 line radar and the IMU inertial element, and the NUC platform is connected with the Velodyne16 line radar network cable and the Intel realsense camera and the IMU inertial element USB (Universal Serial Bus ).

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides an automatic charging robot for realizing the above-mentioned charging positioning and guiding method. The implementation of the solution provided by the automatic charging robot is similar to that described in the above method, so the specific limitation in one or more embodiments of the automatic charging robot provided below may refer to the limitation of the charging positioning guiding method hereinabove, and will not be repeated herein.

In one exemplary embodiment, as shown in fig. 5, there is provided an automatic charging robot including: an environment awareness module 502, a footable point selection module 504, and a motion trajectory planning module 506, wherein:

the environment sensing module 502 is configured to obtain environment information, and generate a terrain evaluation value according to the environment information; the environment information includes terrain information of a navigation path of the robot from the current position to the charging preset position.

The footable point selection module 504 is configured to obtain a footable point of the robot according to the terrain evaluation value and the reachable range of the robot.

The motion trajectory planning module 506 is configured to generate a continuous sequence of footfalls according to the footable points, evaluate stability of the sequence of footfalls, and plan a motion trajectory of the robot along the navigation path.

In an exemplary embodiment, the environment sensing module is further configured to acquire a terrain height and a slope of each acquisition point in the area between the current position of the robot and the charging preset position; acquiring the topography height of the acquisition point according to the topography height and the interpolation function; the interpolation function is a function describing the average height of the acquisition points; and obtaining terrain evaluation values corresponding to the acquisition points according to the terrain height and the gradient.

In an exemplary embodiment, the footable point selection module is further configured to determine, according to the terrain evaluation value and the reachable range of the robot, whether each acquisition point is reachable by the robot, and if so, the acquisition point is the footable point.

In an exemplary embodiment, the footable point selecting module is further configured to evaluate the footable points according to the current position of the robot, the euclidean distance of the footable points, and the reachable range of the robot, and obtain corresponding evaluation values of the footable points; the evaluation value is used for representing the goodness of the footable point.

In an exemplary embodiment, the motion trail planning module is further configured to determine a current foot drop point according to a current position of the robot, and select a next foot drop point corresponding to the current foot drop point from the available foot drop points according to the current foot drop point; iteratively selecting a foothold until the foothold reaches a charging preset position; and generating a sequence of foothold points according to the selected order of the foothold points.

In an exemplary embodiment, the motion trail planning module is further configured to determine, according to a stability criterion, whether the robot can maintain balance under a specific motion condition according to a support domain generated by the foothold point; if not, the sequence of the foothold points is adjusted until the robot keeps balance at each foothold point, and the motion trail is obtained.

In an exemplary embodiment, the motion trajectory planning module further includes: after the robot reaches a charging preset position along a motion track, entering a preset charging state position and entering a charging state; and judging that the charging state is valid, and if the charging state is invalid, adjusting the posture of the robot until the charging state becomes valid.

The respective modules in the above-described automatic charging robot may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one exemplary embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 6. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a charge positioning guidance method.

It will be appreciated by those skilled in the art that the structure shown in fig. 6 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In an exemplary embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor performing the steps of the method embodiments described above when the computer program is executed.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the method embodiments described above.

In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use, and processing of the related data are required to meet the related regulations.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims (10)

1. A charging positioning guidance method, the method comprising:

acquiring environment information, and generating a terrain evaluation value according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot;

acquiring a footable point of the robot according to the terrain evaluation value and the reachable range of the robot;

and generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence, and planning the motion track of the robot along the navigation path.

2. The method of claim 1, wherein the obtaining environmental information, and generating the terrain assessment value based on the environmental information comprises:

collecting the terrain height and gradient of each collecting point in the area between the current position of the robot and the charging preset position;

acquiring the terrain height of the acquisition point according to the terrain height and the interpolation function; the interpolation function is a function describing the average height of the acquisition points;

and acquiring the terrain evaluation value corresponding to each acquisition point according to the terrain height and the gradient.

3. The method of claim 2, wherein the obtaining the robot's footable point based on the terrain assessment value and the robot's reach comprises:

judging whether each acquisition point is reachable by the robot according to the terrain evaluation value and the reachable range of the robot, and if so, judging that the acquisition point is the footable point;

the method further comprises the steps of:

evaluating the footable points according to the current position of the robot, the Euclidean distance of the footable points and the reachable range of the robot, and obtaining corresponding evaluation values of the footable points; the evaluation value is used for representing the goodness of the footable point.

4. The method of claim 1, wherein the generating a continuous sequence of foothold from the footable points comprises:

determining a current foot drop point according to the current position of the robot, and selecting a next foot drop point corresponding to the current foot drop point from the foot drop points according to the current foot drop point; iteratively selecting the foothold until the foothold reaches the charging preset position;

and generating the foothold sequence according to the selected sequence of the foothold.

5. The method of claim 1, wherein the evaluating the stability of the sequence of foothold points, planning a trajectory of the robot along the navigation path comprises:

judging whether the robot can keep balance under a specific motion condition according to a support domain generated by the foothold point and a stability criterion;

if not, the foot drop point sequence is adjusted until the robot keeps balance at each foot drop point, and the motion trail is obtained.

6. The method according to any one of claims 1 to 5, further comprising:

after the robot reaches the charging preset position along the motion trail, entering a preset charging state position and entering a charging state;

and judging that the charging state is valid, and if the charging state is invalid, adjusting the posture of the robot until the charging state becomes valid.

7. An automatic charging robot, characterized in that the automatic charging robot comprises:

the environment sensing module is used for acquiring environment information and generating a terrain evaluation value according to the environment information; the environment information comprises terrain information of a navigation path from the current position to the charging preset position of the robot;

the foot-drop point selection module is used for acquiring foot-drop points of the robot according to the terrain evaluation value and the reachable range of the robot;

and the motion track planning module is used for generating a continuous foothold sequence according to the foothold, evaluating the stability of the foothold sequence and planning the motion track of the robot along the navigation path.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.