Motion control method and system of robot

Abstract

The invention discloses a robot motion control method and system, and relates to the technical field of robot motion control, and the method comprises the following steps: S1, the robot motion control method is applied to a quadruped robot, and the reachable range of the foot end of each leg is analyzed through forward kinematics; a joint angle needed for achieving the planned foot end position is obtained through inverse kinematics, the quadruped robot is simplified into a single rigid body model, and kinematics analysis is conducted on the single rigid body model obtained through simplification. The invention provides a robot motion control method and system, the robot motion control method is applied to a quadruped robot, forward kinematics analysis and inverse kinematics analysis are carried out on the quadruped robot, radar point cloud data are obtained through a laser radar carried by the quadruped robot, and a three-dimensional point cloud map is constructed based on the radar point cloud data. Map conversion and optimization operation are carried out on the constructed three-dimensional point cloud map in a cost map construction mode, and a transition function between different gaits is designed.

Description

Technical Field

[0001] The present invention relates to the technical field of robot motion control, and in particular to a robot motion control method and system. Background Art

[0002] With the development of science and technology, intelligent robots have also been widely developed. In the Chinese patent with application number 201711281609.0, "a robot motion control method, robot and system are disclosed, including: step S200, the robot receives a robot motion control file, the robot motion control file includes a robot script and a motion control configuration file, the robot script includes a robot-specific action function; step S300, the robot parses the robot script to obtain the robot-specific action function, and generates at least one program instruction according to the robot-specific action function and the motion control configuration file; step S400, the robot performs corresponding actions according to each of the program instructions. The present invention can provide a consistent communication interface and a unified programming language for the operation control of various robots, and has versatility and flexibility."; This existing technology only solves the problem that the robots of various manufacturers have different morphologies, and each manufacturer controls its own robots through its own private protocols and private languages, and lacks a consistent communication interface and a unified programming language. It does not take into account that when controlling the motion of a quadruped robot, a map of the environment in which the quadruped robot is located should be constructed first to facilitate subsequent route trajectory planning, and gait planning of the quadruped robot is required to avoid direct gait switching that causes sudden phase changes or dead zones between oscillators. During the movement of the quadruped robot, the quadruped robot needs to be detected for ground contact to obtain information on the terrain in which the quadruped robot is located and the hardness of the terrain, so as to facilitate subsequent gait adjustments and improve the motion stability of the quadruped robot in different terrain environments. In addition, a strategy for accidental ground contact of the quadruped robot needs to be designed to deal with the situation in which the quadruped robot accidentally touches the ground. Summary of the invention

[0003] The object of the present invention is to provide a robot motion control method and system to solve the problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solution: a robot motion control method, comprising the following steps: S1: A robot motion control method is applied to a quadruped robot. The reachable range of each leg end is analyzed by forward kinematics, and the joint angles required to achieve the planned foot end position are obtained by inverse kinematics. The quadruped robot is simplified into a single rigid body model, and the simplified single rigid body model is kinematically analyzed. S2: Based on the radar point cloud data obtained by the laser radar carried by the quadruped robot, a point cloud map of the environment in which the quadruped robot is located is constructed based on the acquired radar point cloud data, and a map conversion operation is performed on the constructed environment point cloud map by constructing a cost map, and the converted map is optimized, and the position information of the quadruped robot in the optimized map is calculated; S3: Perform gait planning for the quadruped robot and design transition functions between different gaits to avoid sudden phase changes or dead zones between oscillators caused by direct gait switching, and achieve smooth transitions between gaits so that the quadruped robot can adapt to different subsequent terrains. Perform ground contact detection for the quadruped robot and set an unexpected ground contact strategy for the quadruped robot to deal with early or delayed ground contact. S4: The terrain classifier is designed through sample training, so as to obtain the terrain where the quadruped robot is located and the hardness of the corresponding terrain, and then adjust the gait planning of the quadruped robot to improve the motion stability of the quadruped robot in different terrain environments.

[0005] Preferably, step S1 further includes analyzing the reach of each leg end through forward kinematics, and the specific operation is to obtain the size parameters and other related parameters of the quadruped robot through the quadruped robot design drawings and instruction manual, and establish the DH coordinate system of the quadruped robot based on the parameter information of the quadruped robot, which is defined as , and define the fuselage base coordinate system as ,in , respectively represent the left front, right front, right rear and left rear legs of the quadruped robot, where , represents the DH coordinate system at the top of each leg, the joint and the foot end node, and the foot end coordinate system of each leg of the quadruped robot To the fuselage base coordinate system The expression of the homogeneous transformation matrix is ​​as follows:

[0006] in, For the coordinate system To coordinate system The transformation matrix, the parameters of which Take 1 to 3 respectively, get each transformation matrix, and then get the quadruped robot The position of the foot end of the leg relative to the fuselage base coordinate system is expressed as follows:

[0007] In the formula They represent the physical parameters describing the size of the quadruped robot, They represent the rotation angles of the quadruped robot’s hip abduction, hip flexion and extension, and knee flexion and extension, respectively. and Respectively represent symbolic variables, and the value expressions are as follows:

[0008] Thus, the reachable range of each leg foot end is obtained.

[0009] Preferably, step S1 further comprises obtaining the joint angle required to realize the planned foot end position by inverse kinematics, specifically, applying the inverse transformation method to the quadruped robot. The expression of the position of the foot end of each leg relative to the body base coordinate system can be used to obtain the four groups of robots. The rotation angles of hip abduction, hip flexion and extension, and knee flexion and extension on the four legs are calculated, and the quadruped robot is simplified into a single rigid body model, in which the fuselage is regarded as the center of mass, and the four legs are regarded as parts that move with the center of mass and rotate around the center of mass. According to Newton's second law, the translation function of the quadruped robot is established, and its specific expression is as follows:

[0010] In the formula, The quadruped robot The reaction force at the foot end of the leg, represents the total mass of the quadruped robot, represents the acceleration of the quadruped robot’s center of mass, Represents the acceleration due to gravity. According to the law of conservation of angular momentum, the rotation function of the quadruped robot is established. Its specific expression is as follows:

[0011] In the formula, Represents the center of mass to the quadruped robot The radius vector of the foot end of the leg, represents the inertia tensor of the rigid body, represents the angular acceleration of the quadruped robot body, It represents the angular velocity of the quadruped robot body, and the kinematic analysis is performed through the constructed translation function and rotation function of the quadruped robot.

[0012] Preferably, step S2 further includes acquiring radar point cloud data through a laser radar carried by the quadruped robot, and constructing a point cloud map of the environment in which the quadruped robot is located based on the acquired radar point cloud data. The specific operation is to calculate the smoothness of each point in the radar point cloud of the current frame, and the specific calculation formula is as follows:

[0013] In the formula, Indicate point The smoothness, Indicate point and the set of adjacent points, represents the radar coordinate system, Indicates The midpoint of the point cloud map in the radar coordinate system in the scanning cycle The coordinates of Indicates The midpoint of the point cloud map in the radar coordinate system in the scanning cycle The coordinates of adjacent points are stored in the edge feature point cloud. The edge lines and feature planes are extracted from the acquired feature points. Assuming that the point is the edge feature point, in In a scanning cycle, obtain the distance point in the point cloud The nearest point, denoted as point , in In a scanning cycle, obtain the distance point in the point cloud closest and different from point Point ,point With point The line connecting the The edge line is obtained by calculating the coordinates. The distance to the edge line is In a scanning cycle, obtain the distance point in the point cloud closest and different from point and Point Point ,point ,point and Point The plane composed of points The characteristic plane of The distance to the feature plane is calculated, and the feature points in two adjacent scanning cycles are matched by the scan-to-scan method to obtain a low-precision radar odometer. Based on the paired feature points, the displacement relationship of the feature point pose is obtained by the difference calculation method, and the feature point cloud is corrected for motion distortion. The scan-to-map method is used for high-precision positioning. The pose information of the low-precision radar odometer is used as the initial pose value, and the feature point cloud is matched with the actual map to obtain a high-precision radar odometer. The pose data of the low-precision radar odometer and the pose data of the high-precision radar odometer are fused through the interpolation process to obtain odometer information with higher update speed and accuracy. The odometer information is read and reproduced through the PCL library, converted into three-dimensional point cloud information, and a 3DSLAM point cloud map is constructed.

[0014] Preferably, step S2 also includes performing a map conversion operation on the 3DSLAM point cloud map by constructing a cost map, and the specific operation is to construct a global map layer cost map through the costmap_2d plug-in tool, reflect environmental information in the form of coordinates, perform obstacle detection through lidar, and compare it with the global map layer cost map information, construct an obstacle layer cost map, and reflect obstacle information in coordinates different from the global map layer. On the basis of the obstacle layer cost map, an expansion radius is set for each obstacle as a warning area for collision, and an expansion layer cost map is obtained. The global map layer cost map, the obstacle layer cost map and the expansion layer cost map are superimposed to obtain a cost map after the point cloud map is converted, and the converted cost map is optimized using GIMP software to remove irrelevant environmental noise, and the position and posture of the quadruped robot in the map are estimated by an adaptive Monte Carlo positioning algorithm.

[0015] Preferably, the step S3 also includes gait planning for the quadruped robot, and the specific operation is to define the time required for the quadruped robot to complete a movement gait as the gait cycle, including the completion time of the stance phase and the completion time of the swing phase, and divide the completion time of the stance phase by the gait cycle to obtain the duty cycle parameter of the gait planning of the quadruped robot. The gait of the quadruped robot can be adjusted by adjusting the duty cycle parameter, and in order to avoid the phase mutation or dead zone between oscillators when the quadruped robot directly switches gaits, a phase transition function between different gaits is designed, and its specific expression is as follows:

[0016] In the formula, Indicates the position of each leg of the quadruped robot The phase of the moment, represents the start time of gait transition, Indicates the end time of gait transition, represents the phase of each leg of the quadruped robot at the start time, Indicates the phase of each leg of the quadruped robot at the end time, so that the quadruped robot can smoothly switch gaits when adapting to different terrains.

[0017] Preferably, step S3 further comprises performing ground contact detection on the quadruped robot, specifically, performing ground contact detection in combination with external ground contact sensor information and internal state information of the quadruped robot, wherein the external ground contact sensor information is obtained through a Hall sensor installed at the foot end of the quadruped robot and a magnet block installed at the sole of the foot, specifically, when the legs of the quadruped robot enter a standing state from a swinging state, the relative angle between the sole of the foot and the ground gradually decreases, so that the relative distance between the Hall sensor and the magnet block changes accordingly, thereby causing a change in magnetic flux, which is ultimately reflected as a change in output voltage, wherein the external ground contact sensor information is also obtained through a pressure sensor installed on the bottom surface of the sole block of the quadruped robot, and when the sole of the quadruped robot touches the ground, the pressure sensor detects the pressure applied by the ground to the sole of the foot, and reflects it as an output voltage. Output voltage, wherein the internal state information is specifically obtained through the output torque of the joint motor of the quadruped robot, thereby realizing the touchdown detection of the quadruped robot in the planned gait pattern, and setting an unexpected touchdown strategy for the quadruped robot to deal with the situation that the quadruped robot touches the ground in advance or delays the ground. Specifically, when it is detected that the quadruped robot touches the ground in advance or delays the ground, the time of the early or delayed touchdown is obtained, and the difference between the unexpected and expected touchdown times is calculated based on it, and the calculation result is used to recalculate the phase progress in the current gait cycle, and the swing time of the quadruped robot leg is adjusted accordingly to deal with the early or delayed touchdown of the foot end, and according to the updated phase progress, the landing point position of the foot end of the quadruped robot leg is re-determined, and the swing trajectory is re-planned through kinematic analysis.

[0018] Preferably, step S4 also includes designing a terrain classifier by sample training, so as to facilitate obtaining the terrain where the quadruped robot is located and the hardness of the corresponding terrain. The specific operation is to select various ground medium samples with different hardness, obtain the output voltages of the Hall sensor and the pressure sensor installed on the quadruped robot, use the output results of the two groups of sensors as the basis for ground medium classification, and arrange the output voltages of the pressure sensor in ascending order to form an output voltage sequence, perform statistical analysis on the output voltage sequence, and obtain the characteristic values ​​of the terrain classifier, which are the mean value, standard deviation, median and mode, respectively, which are used as the basis for classification of ground media with different hardness. The classification results are defined as follows:

[0019] Therefore, the terrain in which the quadruped robot is located and the hardness of the corresponding terrain are determined through the designed terrain classifier. Combined with expert experience, the gait planning scheme of the quadruped robot under various terrains and terrains of different hardness is set up, and then the gait planning of the quadruped robot is adjusted, so as to achieve flexible adjustment of the gait of the quadruped robot and improve the movement stability of the quadruped robot in different terrain environments.

[0020] A robot motion control system includes a motion analysis module, wherein the motion analysis module analyzes the reachable range of each leg foot end through forward kinematics, obtains the joint angle required to achieve the planned foot end position through inverse kinematics, simplifies the quadruped robot into a single rigid body model, and performs kinematic analysis on the simplified single rigid body model; An environment map construction module, which obtains radar point cloud data through a laser radar carried by the quadruped robot, and constructs a point cloud map of the environment in which the quadruped robot is located based on the acquired radar point cloud data, performs map conversion and optimization operations on the constructed environment point cloud map, and calculates the position information of the quadruped robot in the optimized map; A ground touchdown detection module, which performs gait planning for the quadruped robot and designs transition functions between different gaits to achieve smooth transitions between gaits, performs ground touchdown detection on the quadruped robot, and sets an unexpected ground touchdown strategy for the quadruped robot to deal with the situation where the quadruped robot touches the ground early or late; The adaptive control module designs a terrain classifier by sample training, so as to obtain the terrain where the quadruped robot is located and the hardness of the corresponding terrain, and then adjust the gait planning of the quadruped robot, so as to improve the motion stability of the quadruped robot in different terrain environments.

[0021] Compared with the prior art, the beneficial effects of the present invention at least include: the present invention proposes a robot motion control method and system, a robot motion control method is applied to a quadruped robot, forward kinematics analysis and inverse kinematics analysis are performed on the quadruped robot, radar point cloud data are obtained through a laser radar carried by the quadruped robot, and a three-dimensional point cloud map is constructed based on the data, map conversion and optimization operations are performed on the constructed three-dimensional point cloud map by constructing a cost map, and a transition function between different gaits is designed to avoid the situation where the phase between oscillators is suddenly changed or dead zone is caused by direct gait switching, so as to achieve smooth conversion between gaits, and the quadruped robot is provided with a touchdown detection and an unexpected touchdown strategy to deal with the situation where the quadruped robot touches the ground early or late, and the gait planning is re-adjusted, and a terrain classifier is designed by sample training, so as to facilitate the acquisition of the terrain where the quadruped robot is located and the hardness of the corresponding terrain, and then the gait planning of the quadruped robot is adjusted, so as to improve the motion stability of the quadruped robot in different terrain environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic flow chart of a robot motion control method provided by an embodiment of the present invention; Figure 2 A schematic diagram of a motion control system flow of a robot provided by an embodiment of the present invention.

[0023] In the figure: 101, motion analysis module; 102, environment map construction module; 103, ground contact detection module; 104, adaptive control module. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] See also Figure 1-Figure 2 The present invention provides a technical solution: a robot motion control method, comprising the following steps: S1: A robot motion control method is applied to a quadruped robot. The reachable range of each leg end is analyzed by forward kinematics, and the joint angles required to achieve the planned foot end position are obtained by inverse kinematics. The quadruped robot is simplified into a single rigid body model, and the simplified single rigid body model is kinematically analyzed. S2: Based on the radar point cloud data obtained by the laser radar carried by the quadruped robot, a point cloud map of the environment in which the quadruped robot is located is constructed based on the acquired radar point cloud data, and a map conversion operation is performed on the constructed environment point cloud map by constructing a cost map, and the converted map is optimized, and the position information of the quadruped robot in the optimized map is calculated; S3: Perform gait planning for the quadruped robot and design transition functions between different gaits to avoid sudden phase changes or dead zones between oscillators caused by direct gait switching, and achieve smooth transitions between gaits so that the quadruped robot can adapt to different subsequent terrains. Perform ground contact detection for the quadruped robot and set an unexpected ground contact strategy for the quadruped robot to deal with early or delayed ground contact. S4: The terrain classifier is designed through sample training, so as to obtain the terrain where the quadruped robot is located and the hardness of the corresponding terrain, and then adjust the gait planning of the quadruped robot to improve the motion stability of the quadruped robot in different terrain environments.

[0026] Step S1 also includes analyzing the reach of each leg end through positive kinematics. The specific operation is to obtain the size parameters and other related parameters of the quadruped robot through the quadruped robot design drawings and instruction manual, and establish the DH coordinate system of the quadruped robot based on the parameter information of the quadruped robot, which is defined as , and define the fuselage base coordinate system as ,in , respectively represent the left front, right front, right rear and left rear legs of the quadruped robot, where , represents the DH coordinate system at the top of each leg, the joint and the foot end node, and the foot end coordinate system of each leg of the quadruped robot To the fuselage base coordinate system The expression of the homogeneous transformation matrix is ​​as follows:

[0027] in, For the coordinate system To coordinate system The transformation matrix, the parameters of which Take 1 to 3 respectively, get each transformation matrix, and then get the quadruped robot The position of the foot end of the leg relative to the fuselage base coordinate system is expressed as follows:

[0028] In the formula They represent the physical parameters describing the size of the quadruped robot, They represent the rotation angles of the quadruped robot’s hip abduction, hip flexion and extension, and knee flexion and extension, respectively. and Respectively represent symbolic variables, and the value expressions are as follows:

[0029] Thus, the reachable range of each leg foot end is obtained; Step S1 also includes obtaining the joint angles required to achieve the planned foot end position through inverse kinematics, specifically applying the inverse transformation method to the quadruped robot. The expression of the position of the foot end of each leg relative to the body base coordinate system can be used to obtain the four groups of robots. The rotation angles of hip abduction, hip flexion and extension, and knee flexion and extension on the four legs are calculated, and the quadruped robot is simplified into a single rigid body model, in which the fuselage is regarded as the center of mass, and the four legs are regarded as parts that move with the center of mass and rotate around the center of mass. According to Newton's second law, the translation function of the quadruped robot is established, and its specific expression is as follows:

[0030] In the formula, The quadruped robot The reaction force at the foot end of the leg, represents the total mass of the quadruped robot, represents the acceleration of the quadruped robot’s center of mass, Represents the acceleration due to gravity. According to the law of conservation of angular momentum, the rotation function of the quadruped robot is established. Its specific expression is as follows:

[0031] In the formula, Represents the center of mass to the quadruped robot The radius vector of the foot end of the leg, represents the inertia tensor of the rigid body, represents the angular acceleration of the quadruped robot body, The angular velocity of the quadruped robot body is expressed, and the kinematic analysis is performed through the constructed translation function and rotation function of the quadruped robot; Step S2 also includes obtaining radar point cloud data through the laser radar carried by the quadruped robot, and constructing a point cloud map of the environment in which the quadruped robot is located based on the obtained radar point cloud data. The specific operation is to calculate the smoothness of each point in the radar point cloud of the current frame. The specific calculation formula is as follows:

[0032] In the formula, Indicate point The smoothness, Indicate point and the set of adjacent points, represents the radar coordinate system, Indicates The midpoint of the point cloud map in the radar coordinate system in the scanning cycle The coordinates of Indicates The midpoint of the point cloud map in the radar coordinate system in the scanning cycle The coordinates of adjacent points are stored in the edge feature point cloud. The edge lines and feature planes are extracted from the acquired feature points. Assuming that the point is the edge feature point, in In a scanning cycle, obtain the distance point in the point cloud The nearest point, denoted as point , in In a scanning cycle, obtain the distance point in the point cloud closest and different from point Point ,point With point The line connecting the The edge line is obtained by calculating the coordinates. The distance to the edge line is In a scanning cycle, obtain the distance point in the point cloud closest and different from point and Point Point ,point ,point and Point The plane composed of points The characteristic plane of The distance to the feature plane is obtained by matching the feature points in two adjacent scanning cycles through the scan-to-scan method to obtain a low-precision radar odometer. Based on the paired feature points, the displacement relationship of the feature point pose is obtained through the difference calculation method, and the motion distortion of the feature point cloud is corrected. The scan-to-map method is used for high-precision positioning. The pose information of the low-precision radar odometer is used as the initial pose value, and the feature point cloud is matched with the actual map to obtain a high-precision radar odometer. The pose data of the low-precision radar odometer and the pose data of the high-precision radar odometer are fused through the interpolation process to obtain odometer information with high update speed and accuracy. The odometer information is read and reproduced through the PCL library, converted into three-dimensional point cloud information, and a 3DSLAM point cloud map is constructed. Step S2 also includes performing a map conversion operation on the 3DSLAM point cloud map by constructing a cost map, and the specific operation is to construct a global map layer cost map through the costmap_2d plug-in tool, reflect environmental information in the form of coordinates, detect obstacles through laser radar, and compare it with the global map layer cost map information, construct an obstacle layer cost map, and reflect obstacle information in coordinates different from the global map layer. On the basis of the obstacle layer cost map, an expansion radius is set for each obstacle as a warning area for collision, and an expansion layer cost map is obtained. The global map layer cost map, the obstacle layer cost map and the expansion layer cost map are superimposed to obtain a cost map after the point cloud map is converted, and the converted cost map is optimized using GIMP software to remove irrelevant environmental noise, and the position and posture of the quadruped robot in the map are estimated by an adaptive Monte Carlo positioning algorithm; Step S3 also includes gait planning for the quadruped robot. The specific operation is to define the time required for the quadruped robot to complete a movement gait as the gait cycle, including the completion time of the stance phase and the completion time of the swing phase. The completion time of the stance phase is divided by the gait cycle to obtain the duty cycle parameter of the gait planning of the quadruped robot. The gait of the quadruped robot can be adjusted by adjusting the duty cycle parameter. In order to avoid the phase mutation or dead zone between oscillators when the quadruped robot directly switches gaits, a phase transition function between different gaits is designed, and its specific expression is as follows:

[0033] In the formula, Indicates the position of each leg of the quadruped robot The phase of the moment, represents the start time of gait transition, Indicates the end time of gait transition, represents the phase of each leg of the quadruped robot at the start time, Indicates the phase of each leg of the quadruped robot at the end time, so that the quadruped robot can smoothly switch gaits when adapting to different terrains; Step S3 also includes performing ground touchdown detection on the quadruped robot, specifically, performing ground touchdown detection in combination with external ground touchdown sensor information and internal state information of the quadruped robot, wherein the external ground touchdown sensor information is obtained through a Hall sensor installed at the foot end of the quadruped robot and a magnet block installed at the sole of the foot. Specifically, when the legs of the quadruped robot enter a standing state from a swinging state, the relative angle between the sole of the foot and the ground gradually decreases, so that the relative distance between the Hall sensor and the magnet block changes accordingly, thereby causing a change in magnetic flux, which is ultimately reflected as a change in the output voltage. The external ground touchdown sensor information is also obtained through a pressure sensor installed on the bottom surface of the sole block of the quadruped robot. When the sole of the quadruped robot touches the ground, the pressure sensor detects the pressure applied by the ground to the sole of the foot, and reflects it as an output voltage. , wherein the internal state information is specifically obtained through the output torque of the joint motor of the quadruped robot, so as to realize the touchdown detection of the quadruped robot in the planned gait mode, and set an unexpected touchdown strategy for the quadruped robot to deal with the situation that the quadruped robot touches the ground in advance or delays the ground. Specifically, when the quadruped robot is detected to have touched the ground in advance or delays, the time of the early or delayed touchdown is obtained, and the difference between the unexpected and expected touchdown times is calculated based on the early or delayed touchdown time. The calculation result is used to recalculate the phase progress in the current gait cycle, and the swing time of the quadruped robot leg is adjusted accordingly to deal with the early or delayed touchdown of the foot end. According to the updated phase progress, the landing point position of the foot end of the quadruped robot leg is re-determined, and the swing trajectory is re-planned through kinematic analysis; Step S4 also includes designing a terrain classifier by sample training, so as to facilitate the acquisition of the terrain where the quadruped robot is located and the hardness of the corresponding terrain. The specific operation is to select various ground medium samples with different hardness, obtain the output voltages of the Hall sensor and the pressure sensor installed on the quadruped robot, use the output results of the two groups of sensors as the basis for ground medium classification, and arrange the output voltages of the pressure sensor in ascending order to form an output voltage sequence, perform statistical analysis on the output voltage sequence, and obtain the characteristic values ​​of the terrain classifier, which are the mean, standard deviation, median and mode, respectively, which are used as the basis for classification of ground media with different hardness. The classification results are defined as follows:

[0034] The terrain classifier designed is used to determine the terrain where the quadruped robot is located and the hardness of the corresponding terrain. Based on expert experience, the gait planning schemes of the quadruped robot under various terrains and terrains of different hardness are set up, and then the gait planning of the quadruped robot is adjusted, thereby realizing flexible adjustment of the gait of the quadruped robot and improving the motion stability of the quadruped robot in different terrain environments. A robot motion control system includes a motion analysis module 101, which analyzes the reachable range of each leg foot end through forward kinematics, obtains the joint angle required to achieve the planned foot end position through inverse kinematics, simplifies the quadruped robot into a single rigid body model, and performs kinematic analysis on the simplified single rigid body model; The environment map construction module 102 obtains radar point cloud data through the laser radar carried by the quadruped robot, and constructs a point cloud map of the environment where the quadruped robot is located based on the acquired radar point cloud data, and performs map conversion and optimization operations on the constructed environment point cloud map, and calculates the position information of the quadruped robot in the optimized map; A ground contact detection module 103, which performs gait planning for the quadruped robot and designs transition functions between different gaits to achieve smooth transitions between gaits, and performs ground contact detection on the quadruped robot, and sets an unexpected ground contact strategy for the quadruped robot to deal with the situation where the quadruped robot touches the ground early or late; The adaptive control module 104 designs a terrain classifier by means of sample training, so as to obtain the terrain where the quadruped robot is located and the hardness of the corresponding terrain, and then adjust the gait planning of the quadruped robot, so as to improve the movement stability of the quadruped robot in different terrain environments.

[0035] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0036] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A robot motion control method, characterized in that The following steps are involved: S1: A robot motion control method is applied to a quadruped robot. The reachable range of each leg end is analyzed by forward kinematics, and the joint angles required to achieve the planned foot end position are obtained by inverse kinematics. The quadruped robot is simplified into a single rigid body model, and the simplified single rigid body model is kinematically analyzed. S2: Based on the radar point cloud data obtained by the laser radar carried by the quadruped robot, a point cloud map of the environment in which the quadruped robot is located is constructed based on the acquired radar point cloud data, and a map conversion operation is performed on the constructed environment point cloud map by constructing a cost map, and the converted map is optimized, and the position information of the quadruped robot in the optimized map is calculated; S3: Perform gait planning for the quadruped robot and design transition functions between different gaits to avoid sudden phase changes or dead zones between oscillators caused by direct gait switching, and achieve smooth transitions between gaits so that the quadruped robot can adapt to different subsequent terrains. Perform ground contact detection for the quadruped robot and set an unexpected ground contact strategy for the quadruped robot to deal with early or delayed ground contact. S4: The terrain classifier is designed through sample training, so as to obtain the terrain where the quadruped robot is located and the hardness of the corresponding terrain, and then adjust the gait planning of the quadruped robot to improve the motion stability of the quadruped robot in different terrain environments.

2. A robot motion control method according to claim 1, characterized in that: The step S1 also includes analyzing the reach of each leg end through positive kinematics. The specific operation is to obtain the size parameters and other related parameters of the quadruped robot through the quadruped robot design drawings and instruction manual, and establish the DH coordinate system of the quadruped robot based on the parameter information of the quadruped robot, which is defined as , and define the fuselage base coordinate system as ,in , respectively represent the left front, right front, right rear and left rear legs of the quadruped robot, where , represents the DH coordinate system at the top of the leg, the joints, and the foot nodes on each leg.

3. The robot motion control method according to claim 1, characterized in that: The step S1 also includes obtaining the joint angles required to achieve the planned foot end position through inverse kinematics, specifically applying the inverse transformation method to the quadruped robot. The expression of the position of the foot end of each leg relative to the body base coordinate system can be used to obtain the four groups of robots. The rotation angles of hip abduction, hip flexion and extension, and knee flexion and extension on the four legs are calculated, and the quadruped robot is simplified into a single rigid body model, in which the fuselage is regarded as the center of mass, and the four legs are regarded as the parts that translate with the center of mass and rotate around the center of mass. According to Newton's second law, the translation function of the quadruped robot is established, and according to the law of conservation of angular momentum, the rotation function of the quadruped robot is established. Kinematic analysis is performed through the constructed translation function and rotation function of the quadruped robot.

4. The robot motion control method according to claim 1, characterized in that: The step S2 also includes obtaining radar point cloud data through the laser radar carried by the quadruped robot, and constructing a point cloud map of the environment in which the quadruped robot is located based on the obtained radar point cloud data. The specific operation is to calculate the smoothness of each point in the radar point cloud of the current frame, and set a smoothness threshold. When the calculation result of the point smoothness is greater than the set smoothness threshold, the point is judged to be a plane feature point and stored in the plane feature point point cloud for publication. Otherwise, it is judged to be an edge feature point and stored in the edge feature point point cloud for publication. The edge line and feature plane are extracted from the obtained feature points, and the feature points under two adjacent scanning cycles are matched by the scan-to-scan method. A low-precision radar odometer is obtained by matching, and based on the paired feature points, the displacement relationship of the feature point pose is obtained by the difference calculation method, and the motion distortion of the feature point cloud is corrected. The scan-to-map method is used for high-precision positioning. The pose information of the low-precision radar odometer is used as the initial pose value, and the feature point cloud is matched with the actual map to obtain a high-precision radar odometer. The pose data of the low-precision radar odometer and the pose data of the high-precision radar odometer are fused through the interpolation process to obtain the odometer information with higher update speed and accuracy. The odometer information is read and reproduced through the PCL library, converted into three-dimensional point cloud information, and a 3DSLAM point cloud map is constructed.

5. The robot motion control method according to claim 1, characterized in that: The step S2 also includes performing a map conversion operation on the 3DSLAM point cloud map by constructing a cost map, and the specific operation is to construct a global map layer cost map through the costmap_2d plug-in tool, reflect environmental information in the form of coordinates, perform obstacle detection through a laser radar, and compare it with the global map layer cost map information, construct an obstacle layer cost map, and reflect obstacle information in coordinates different from the global map layer. On the basis of the obstacle layer cost map, an expansion radius is set for each obstacle as a warning area for collision, and an expansion layer cost map is obtained. The global map layer cost map, the obstacle layer cost map and the expansion layer cost map are superimposed to obtain a cost map after the point cloud map is converted, and the converted cost map is optimized using GIMP software to remove irrelevant environmental noise, and the position and posture of the quadruped robot in the map are estimated by an adaptive Monte Carlo positioning algorithm.

6. The robot motion control method according to claim 1, characterized in that: The step S3 also includes gait planning for the quadruped robot. The specific operation is to define the time required for the quadruped robot to complete a movement gait as a gait cycle, including the completion time of the stance phase and the completion time of the swing phase. The completion time of the stance phase is divided by the gait cycle to obtain the duty cycle parameter of the gait planning of the quadruped robot. The gait of the quadruped robot can be adjusted by adjusting the duty cycle parameter. In order to avoid sudden phase changes or dead zones between oscillators when the quadruped robot directly switches gaits, a phase transition function between different gaits is designed to facilitate the quadruped robot to smoothly switch gaits when adapting to different terrains.

7. The robot motion control method according to claim 1, characterized in that: The step S3 also includes performing ground touchdown detection on the quadruped robot, specifically, performing ground touchdown detection in combination with external ground touchdown sensor information and internal state information of the quadruped robot, wherein the external ground touchdown sensor information is obtained through a Hall sensor installed at the foot end of the quadruped robot and a magnet block installed on the sole of the foot, wherein the external ground touchdown sensor information is also obtained through a pressure sensor installed on the bottom surface of the sole block of the quadruped robot, wherein the internal state information is specifically obtained through the output torque of the joint motor of the quadruped robot, thereby realizing ground touchdown detection of the quadruped robot in the planned gait pattern, and setting an unexpected ground touchdown strategy for the quadruped robot to deal with the situation where the quadruped robot touches the ground early or delayed.

8. The robot motion control method according to claim 1, characterized in that: The step S4 also includes designing a terrain classifier by sample training, so as to facilitate the acquisition of the terrain where the quadruped robot is located and the hardness of the corresponding terrain. The specific operation is to select various ground medium samples with different hardness, obtain the output voltages of the Hall sensor and the pressure sensor installed on the quadruped robot, use the output results of the two groups of sensors as the basis for ground medium classification, and arrange the output voltages of the pressure sensor in ascending order to form an output voltage sequence, perform statistical analysis on the output voltage sequence, and obtain the characteristic values ​​of the terrain classifier, which are the mean, standard deviation, median and mode, respectively, which are used as the basis for classifying ground media with different hardness, so as to determine the terrain where the quadruped robot is located and the hardness information of the corresponding terrain through the designed terrain classifier, and set the quadruped robot gait planning scheme under various terrains and terrains with different hardnesses in combination with expert experience, and then adjust the quadruped robot gait planning, so as to realize flexible adjustment of the quadruped robot gait and improve the motion stability of the quadruped robot in different terrain environments.

9. A robot motion control system, characterized in that: The method comprises a motion analysis module (101), wherein the motion analysis module (101) analyzes the reachable range of the foot end of each leg through forward kinematics, obtains the joint angle required to achieve the planned foot end position through inverse kinematics, simplifies the quadruped robot into a single rigid body model, and performs kinematic analysis on the simplified single rigid body model; An environment map construction module (102), wherein the environment map construction module (102) obtains radar point cloud data through a laser radar carried by the quadruped robot, and constructs a point cloud map of the environment in which the quadruped robot is located based on the acquired radar point cloud data, and performs map conversion and optimization operations on the constructed environment point cloud map, and calculates the position information of the quadruped robot in the optimized map; A ground contact detection module (103), wherein the ground contact detection module (103) performs gait planning on the quadruped robot and designs transition functions between different gaits to achieve smooth transitions between gaits, and performs ground contact detection on the quadruped robot, and sets an unexpected ground contact strategy for the quadruped robot to deal with situations where the quadruped robot touches the ground early or late; An adaptive control module (104) is provided, wherein the adaptive control module (104) designs a terrain classifier by means of sample training, thereby facilitating acquisition of the terrain in which the quadruped robot is located and the degree of hardness and softness of the corresponding terrain, and then adjusting the gait planning of the quadruped robot, thereby improving the movement stability of the quadruped robot in different terrain environments.

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