Robot motion control method and device, medium and electronic equipment

Abstract

The invention belongs to the technical field of robot control, and relates to a robot motion control method and device, a medium and electronic equipment. The method comprises the steps of obtaining current pose information of a robot and target pose information corresponding to the current pose information; a tracking controller is determined according to the current pose information and the target pose information, and contact force borne by the robot is obtained; a target force is determined based on the contact force and the tracking controller to control motion of the robot based on the target force. According to the robot motion control method and device, on one hand, the motion track does not need to be continuously demonstrated again under the influence of target pose information changes, generalization and accuracy of robot motion control are improved, and accurate contact between the robot and the contact plane is guaranteed; and on the other hand, the requirement for precision of a sensor for collecting pose information and stress information is lowered, a certain fault-tolerant capability is achieved for errors caused by hardware, collision and damage of the robot are avoided, and the robustness of robot motion control is improved.

Description

Technical Field

[0001] The present disclosure belongs to the technical field of robot control, and in particular relates to a robot motion control method, a robot motion control device, a computer-readable storage medium, and an electronic device. Background Art

[0002] Robots, such as robotic arms, are mechanical structures with multiple joints and actuators, commonly used to perform a variety of tasks, such as industrial assembly, material handling, medical surgery, and space exploration. The field of robotic arm motion control focuses on the design and implementation of motion control algorithms and techniques within robotic arm systems. Within this field, researchers and engineers use a variety of control methods and algorithms to achieve different types of motion control, including position-based, velocity-based, and force-based control methods.

[0003] Typically, end-to-end contact is achieved using drag-based teaching methods, or by predicting the contact plane's pose using a visual camera. However, drag-based teaching methods require re-teaching the motion trajectory when the contact plane's pose changes, resulting in poor generalization. The success rate of camera-based methods is limited by the performance of the visual sensor and can easily cause the robot to collide and be damaged, resulting in poor robustness. Summary of the Invention

[0004] To overcome the problems existing in the related art, the present disclosure provides a robot motion control method, a robot motion control device, a computer-readable storage medium, and an electronic device.

[0005] According to a first aspect of an embodiment of the present disclosure, a motion control method for a robot is provided, the method comprising:

[0006] Obtaining the current posture information of the robot and the target posture information corresponding to the current posture information;

[0007] Determining a tracking controller according to the current posture information and the target posture information, and obtaining a contact force on the robot;

[0008] A target force is determined based on the contact force and the tracking controller to control the motion of the robot based on the target force.

[0009] Optionally, the obtaining of the current posture information of the robot and the target posture information corresponding to the current posture information includes:

[0010] Obtaining the current posture information of the robot and the original posture information corresponding to the current posture information;

[0011] The hand-eye calibration technology is used to map the original posture information to obtain the target posture information.

[0012] Optionally, obtaining the contact force applied to the robot includes:

[0013] Obtaining the original force exerted on the robot, and performing initial mapping processing on the original force to obtain an intermediate force;

[0014] The intermediate force is subjected to advanced mapping processing to obtain the contact force.

[0015] Optionally, determining the target force according to the contact force and the tracking controller includes:

[0016] Comparing the contact force with a corresponding first threshold to obtain a first comparison result;

[0017] A target force is determined based on the first comparison result and the tracking controller.

[0018] Optionally, determining the target force according to the first comparison result and the tracking controller includes:

[0019] When the first comparison result is that the contact force is less than the first threshold, determining a target force using the tracking controller;

[0020] When the first comparison result is that the contact force is greater than or equal to the first threshold, a target force is determined according to the current posture information.

[0021] Optionally, determining the target force according to the contact force and the tracking controller includes:

[0022] Comparing the contact force with a corresponding second threshold value to obtain a second comparison result, and acquiring a target model;

[0023] A target force is determined based on the second comparison result, the target model, and the tracking controller.

[0024] Optionally, determining the target force according to the second comparison result, the target model, and the tracking controller includes:

[0025] When the second comparison result is that the contact force is greater than the second threshold, obtaining a first offset parameter using the target model;

[0026] Determining desired pose information according to the first offset parameter, and updating the tracking controller using the desired pose information;

[0027] A target force is determined based on the updated tracking controller.

[0028] Optionally, determining the target force according to the second comparison result, the target model, and the tracking controller includes:

[0029] When the second comparison result is that the contact force is less than or equal to the second threshold, obtaining a second offset parameter using the target model;

[0030] A target force is determined based on the second offset parameter and the tracking controller.

[0031] According to a second aspect of the embodiments of the present disclosure, there is provided a motion control device for a robot, comprising:

[0032] A posture acquisition module is configured to obtain current posture information of the robot and target posture information corresponding to the current posture information;

[0033] a force acquisition module, configured to determine a tracking controller according to the current posture information and the target posture information, and acquire the contact force exerted on the robot;

[0034] A fusion control module is configured to determine a target force according to the contact force and the tracking controller, so as to control the motion of the robot according to the target force.

[0035] Optionally, the posture acquisition module is configured to:

[0036] Obtaining the current posture information of the robot and the original posture information corresponding to the current posture information;

[0037] The hand-eye calibration technology is used to map the original posture information to obtain the target posture information.

[0038] Optionally, the force acquisition module is configured to:

[0039] Obtaining the original force exerted on the robot, and performing initial mapping processing on the original force to obtain an intermediate force;

[0040] The intermediate force is subjected to advanced mapping processing to obtain the contact force.

[0041] Optionally, the fusion control module is configured to:

[0042] Comparing the contact force with a corresponding first threshold to obtain a first comparison result;

[0043] A target force is determined based on the first comparison result and the tracking controller.

[0044] Optionally, the fusion control module is configured to:

[0045] When the first comparison result is that the contact force is less than the first threshold, determining a target force using the tracking controller;

[0046] When the first comparison result is that the contact force is greater than or equal to the first threshold, a target force is determined according to the current posture information.

[0047] Optionally, the fusion control module is configured to:

[0048] Comparing the contact force with a corresponding second threshold value to obtain a second comparison result, and acquiring a target model;

[0049] A target force is determined based on the second comparison result, the target model, and the tracking controller.

[0050] Optionally, the fusion control module is configured to:

[0051] When the second comparison result is that the contact force is greater than the second threshold, obtaining a first offset parameter using the target model;

[0052] Determining desired pose information according to the first offset parameter, and updating the tracking controller using the desired pose information;

[0053] A target force is determined based on the updated tracking controller.

[0054] Optionally, the fusion control module is configured to:

[0055] When the second comparison result is that the contact force is less than or equal to the second threshold, obtaining a second offset parameter using the target model;

[0056] A target force is determined based on the second offset parameter and the tracking controller.

[0057] According to a third aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of any one of the robot motion control methods provided in the first aspect of the present disclosure are implemented.

[0058] According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic device, including:

[0059] processor;

[0060] a memory for storing processor-executable instructions;

[0061] The processor is configured to execute the executable instructions to implement any one of the steps of the robot motion control method provided in the first aspect of the present disclosure.

[0062] The technical solutions provided by the embodiments of the present disclosure may have the following beneficial effects:

[0063] In the method and apparatus provided by the exemplary embodiments of the present disclosure, current posture information and target posture information are used to determine a tracking controller, and the robot's motion is controlled based on the acquired contact force and the tracking controller, providing a robot motion control method that integrates posture information and force information. On the one hand, there is no need to constantly re-teach the motion trajectory due to changes in target posture information, which improves the generalization and accuracy of the robot's motion control and ensures accurate contact between the robot and the contact surface. On the other hand, the accuracy requirements for the sensors that collect posture and force information are reduced, and a certain degree of fault tolerance is provided for errors caused by hardware, avoiding collisions and damage to the robot and improving the robustness of the robot's motion control.

[0064] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0066] Figure 1 The following schematically illustrates a flow chart of a motion control method for a robot in an exemplary embodiment of the present disclosure;

[0067] Figure 2 The following schematically illustrates a flow chart of a method for obtaining current posture information and target posture information in an exemplary embodiment of the present disclosure;

[0068] Figure 3 A schematic flow chart of a method for obtaining contact force in an exemplary embodiment of the present disclosure is shown;

[0069] Figure 4 A schematic flow chart of a method for determining a target force in an exemplary embodiment of the present disclosure is shown;

[0070] Figure 5 A schematic flow chart of a method for further determining target force in an exemplary embodiment of the present disclosure is schematically shown;

[0071] Figure 6 Schematically illustrates a flow chart of another method for determining target force in an exemplary embodiment of the present disclosure;

[0072] Figure 7 Schematically illustrates a flow chart of another method for further determining target force in an exemplary embodiment of the present disclosure;

[0073] Figure 8 A flowchart schematically illustrates another method for further determining target force in an exemplary embodiment of the present disclosure;

[0074] Figure 9 A schematic flow chart schematically illustrates a motion control method for a robot in an application scenario in an exemplary embodiment of the present disclosure;

[0075] Figure 10 A schematic diagram schematically illustrates the structure of a robot in an application scenario in an exemplary embodiment of the present disclosure;

[0076] Figure 11 A schematic flow chart schematically illustrates another robot motion control method in an application scenario in an exemplary embodiment of the present disclosure;

[0077] Figure 12 A schematic structural diagram of a motion control device for a robot in an exemplary embodiment of the present disclosure is shown schematically;

[0078] Figure 13 A schematic structural diagram of another robot motion control device in an exemplary embodiment of the present disclosure is shown;

[0079] Figure 14 The following schematically shows the structure of another robot motion control device in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0080] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

[0081] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the corresponding data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0082] A robot, such as a robotic arm, is a mechanical structure with multiple joints and actuators, and is commonly used to perform various tasks such as industrial assembly, material handling, medical surgery, space exploration, etc.

[0083] The field of robotic motion control focuses on the design and implementation of motion control algorithms and techniques within robotic arm systems. The primary goal of robotic motion control is to enable precise position and posture control of the robotic arm to perform specific tasks. Typically, these tasks include controlling the joint motion of the robotic arm, tracking the trajectory of the end effector, and performing obstacle avoidance and collision detection.

[0084] In the field of motion control of robotic arms, researchers and engineers use various control methods and algorithms to implement different types of motion control, including position-based, velocity-based, and force-based control methods.

[0085] Common control strategies include classic PID control (Proportional-Integral-Derivative Control), trajectory planning, inverse kinematics, dynamic modeling and model predictive control.

[0086] In related technologies, the trajectory of the robot arm moving to the target point can be obtained through teaching, and then the trajectory can be reproduced through tracking control.

[0087] Specifically, the user drags the robotic arm in drag mode to complete the end contact task, and records the joint motion trajectory and end motion trajectory of the robotic arm in the process; finally, the tracking controller is used to control the robotic arm to reproduce and complete the contact task.

[0088] Furthermore, a robot arm end contact method based on a drag teaching method is provided.

[0089] In this method, the robotic arm is dragged by implementing gravity compensation for the robotic arm; then, the researchers drag the robotic arm to complete the contact task and record the angle change curve of each joint of the robotic arm in real time; finally, end contact is achieved using joint position tracking control.

[0090] In addition, visual sensors can be used to obtain target posture information, and then the end tracking movement can be used to move to the target point.

[0091] Specifically, in a robotic arm end-to-end contact scenario, a visual sensor is typically used to obtain the target contact point location, which is then used as the tracking target for the controller. The controller then calculates the corresponding control instructions to drive the robotic arm to track the target.

[0092] Furthermore, a robotic arm feedback control method based on a visual camera is provided.

[0093] In this method, the position and posture of the contact plane are detected and estimated by a visual camera; then, end contact is achieved by using a tracking control method based on PID and dynamic feedforward.

[0094] However, when the posture of the contact plane changes, the drag-based teaching solution requires re-teaching the motion trajectory, resulting in poor generalization.

[0095] Due to hardware limitations, the success rate of vision-based solutions is limited by the performance of the vision sensors. Even with a small error in the identified target point's position and pose, the robotic arm may not reach the target point, or may collide with the contact surface due to the control force generated by the error, causing damage and resulting in poor robustness.

[0096] In order to solve the problems existing in the related art, the present invention provides a motion control method for a robot. Figure 1 FIG. 1 is a flow chart of a motion control method for a robot according to an exemplary embodiment. Figure 1 As shown, the method may include at least the following steps:

[0097] Step S110: Obtain the current posture information of the robot and the target posture information corresponding to the current posture information.

[0098] Step S120: Determine a tracking controller based on the current posture information and the target posture information, and obtain the contact force on the robot.

[0099] Step S130 . Determine a target force based on the contact force and the tracking controller to control the movement of the robot according to the target force.

[0100] In an exemplary embodiment of the present disclosure, a tracking controller is determined using current and target pose information, and the robot's motion is controlled based on the acquired contact force and the tracking controller, providing a robot motion control method that integrates pose information and force information. On the one hand, there is no need to constantly re-teach the motion trajectory based on changes in target pose information, which improves the generalization and accuracy of the robot's motion control and ensures accurate contact between the robot and the contact surface. On the other hand, the accuracy requirements for the sensors that collect pose and force information are reduced, providing a certain degree of fault tolerance for errors caused by hardware, avoiding collisions and damage to the robot, and improving the robustness of the robot's motion control.

[0101] The following is a detailed description of each step of the robot motion control method.

[0102] In step S110 , the current posture information of the robot and the target posture information corresponding to the current posture information are obtained.

[0103] In an exemplary embodiment of the present disclosure, the robot may be a robotic arm, a bipedal robot, a quadrupedal robot, etc., and this exemplary embodiment does not specifically limit this.

[0104] In an alternative embodiment, Figure 2 A flow chart of a method for obtaining current pose information and target pose information is shown in FIG. Figure 2 As shown, the method may at least include the following steps: in step S210, the current posture information of the robot and the original posture information corresponding to the current posture information are obtained.

[0105] In order to obtain the position of the target object, a visual sensor is set in the end contact scene of the robot. The target object can be an object that the robot wants to contact or other objects related to the robot, which is not specifically limited in this exemplary embodiment.

[0106] The visual sensor can perceive and detect the surface of the target object, and analyze it to obtain the corresponding position information and posture information as the original posture information.

[0107] Furthermore, the current position information and posture information representing the end of the robot are obtained as the current posture information, and the current posture information can be obtained by solving the robot kinematic model and joint angles.

[0108] It is worth noting that the current pose information of the robot is the pose information in the robot's base coordinate system, while the original pose information is the pose information in the camera coordinate system.

[0109] In step S220, the original posture information is mapped using the hand-eye calibration technology to obtain the target posture information.

[0110] The hand-eye calibration technology can convert the original pose information in the camera coordinate system into the pose information in the robot base coordinate system as the target pose information.

[0111] Among them, hand-eye calibration is a technology used to unify the coordinate system of the visual system (usually refers to the camera on the robot or robotic arm) and the robot itself, so that the object pose determined by the visual system can be converted to the coordinate system of the robot.

[0112] The main purpose of hand-eye calibration is to realize the transformation of objects between the world coordinate system and the robot coordinate system.

[0113] During calibration, a world coordinate system is usually set up on the work plane, which does not coincide with the robot coordinate system. By calibrating the camera's internal and external parameters, the position of the object in the world coordinate system can be calculated.

[0114] If you need to coordinate the robot with vision, you need to obtain the coordinates of the object in the robot's coordinate system. Hand-eye calibration can be achieved by moving a mobile tool (such as a robotic arm) with a calibration plate to different positions and angles below the camera, and then the camera takes multiple photos of the calibration plate to calculate the hand-eye calibration.

[0115] In this way, the positional relationship between the camera coordinate system and the base coordinate system can be solved, thereby realizing the linkage between the robot and vision.

[0116] There are two main types of hand-eye calibration: Eye-to-Hand and Eye-in-Hand. Eye-to-Hand means the camera is fixed relative to the robot base, while Eye-in-Hand means the camera is fixed to the end of the robotic arm.

[0117] In step S120, a tracking controller is determined according to the current posture information and the target posture information, and the contact force on the robot is obtained.

[0118] In an exemplary embodiment of the present disclosure, in order to control the end of the robot to move to the target position represented by the target posture information to make contact, a tracking controller as shown in formula (1) can be designed:

[0119]

[0120] Among them, the three-dimensional vector Represents the position information in the target pose information, three-dimensional rotation matrix represents the posture information in the target posture information, F represents the target force used to control the robot motion, represents the dynamic model of the robot, the specific form of which can be obtained through dynamic identification; x, R respectively represent the end position and posture of the robot in the current posture information, which are obtained through the robot kinematic model and joint angle solution; k px ,k pr ,k dx ,k dr The parameters of the tracking controller can be selected and set by engineers based on their experience in practice; represents the position of the robot in the base coordinate system, Indicates the speed of the robot's movement; Indicates the rotation angle of the robot; Indicates the angular velocity of the robot.

[0121] However, in actual use, due to temperature drift and calibration errors, the target pose information obtained by the visual sensor has certain errors. Therefore, the target force calculated by the tracking controller shown in formula (1) may drive the robot to collide with the contact surface.

[0122] To avoid this situation, the target force can be determined by integrating the sensing results of the force sensor.

[0123] In an alternative embodiment, Figure 3 A flow chart of the method for obtaining contact force is shown in FIG. Figure 3 As shown, the method may at least include the following steps: in step S310, the original force exerted on the robot is obtained, and the original force is initially mapped to obtain an intermediate force.

[0124] The force sensor at the end of the robot can sense the force in the end coordinate system as the original force, which can be expressed as F eef =[f x ,f y ,f z ] T express.

[0125] In order to obtain the contact force F in the direction of the contact surface con , we can first map the original force at the end to the base coordinate system to obtain the intermediate force.

[0126] In step S320 , an advanced mapping process is performed on the intermediate force to obtain the contact force.

[0127] Furthermore, the intermediate force mapped to the base coordinate system can be mapped to the contact surface coordinate system to obtain the contact force.

[0128] Specifically, the contact force mapping process can be expressed by formula (2):

[0129]

[0130] The rotation matrix satisfies Rotation matrix from the end coordinate system to the base coordinate system It can be obtained through kinematics.

[0131] In step S130 , a target force is determined according to the contact force and the tracking controller to control the motion of the robot according to the target force.

[0132] In an exemplary embodiment of the present disclosure, after the contact force is obtained, the target force may be determined according to the contact force and the tracking controller.

[0133] In an alternative embodiment, Figure 4 A flow chart of a method for determining target force is shown in FIG. Figure 4 As shown, the method may at least include the following steps: in step S410, the contact force is compared with a corresponding first threshold to obtain a first comparison result.

[0134] Here, the first threshold can be expressed as f max express.

[0135] In order to determine a suitable first threshold of contact force, engineers can manually drag the robot arm to contact the contact surface in the teaching mode and record the contact force f along the z-axis of the contact surface at this time. z, the contact force f z Set as the first threshold value f of the contact force in the actual control process max .

[0136] Similarly, the first threshold along the x-axis or y-axis of the contact surface may also be determined in this manner, and this exemplary embodiment does not impose any special limitation thereto.

[0137] In step S420 , a target force is determined according to the first comparison result and the tracking controller.

[0138] In an alternative embodiment, Figure 5 A flow chart of a method for further determining the target force is shown in FIG. Figure 5 As shown, the method may include at least the following steps: in step S510, when the first comparison result is that the contact force is less than the first threshold, the target force is determined by using a tracking controller.

[0139] When the first comparison result is that the contact force is less than the first threshold, for example, the contact force is along the z-axis of the contact surface, the form of the tracking controller remains unchanged, and the target force can be calculated using the tracking controller.

[0140] It is worth noting that when the contact force is along the x-axis or y-axis of the contact surface, the target force can also be calculated using the tracking controller.

[0141] In step S520, when the first comparison result is that the contact force is greater than or equal to the first threshold, the target force is determined according to the current posture information.

[0142] When it is detected that the contact force is greater than the set first threshold, in order to ensure that the robot can maintain contact and prevent collision, the expected position of the tracking controller can be set as the current position.

[0143] Therefore, when the contact force is along the z-axis of the contact surface, the tracking controller can be adjusted to the form shown in formula (3):

[0144]

[0145] Based on this, when the first comparison result is that the contact force is greater than or equal to the first threshold, or the contact force is less than the first threshold, the target force can be determined according to the adjusted tracking controller formula (3).

[0146] In actual use, redundant position quantities can be added at the target position along the normal direction of the contact surface to prevent the robotic arm from failing to touch the contact surface.

[0147] The redundant position amount may be set to data that is the same as the error of the force sensor, or may be set to data that is greater than the error of the force sensor, which is not particularly limited in this exemplary embodiment.

[0148] In an alternative embodiment, Figure 6 A flow chart of another method for determining the target force is shown in FIG. Figure 6 As shown, the method may at least include the following steps: in step S610, the contact force is compared with the corresponding second threshold to obtain a second comparison result, and a target model is obtained.

[0149] The second threshold can be expressed as f d It can be pre-set or determined in other ways, and this exemplary embodiment does not make any special limitation on this.

[0150] Furthermore, a target model may be obtained, which may be an admittance model.

[0151] Among them, admittance control is a control strategy commonly used in robots and other automated systems to make their interaction with the environment more natural and flexible.

[0152] The core idea of ​​this control method is to imitate human behavior and adjust the robot's movement to adapt to changes in external conditions by measuring feedback from the environment and external forces.

[0153] Specifically, admittance control works by measuring the force or displacement between the robot and its environment. It is based on a model, called an "admittance model," that describes how the robot responds to external forces.

[0154] Based on the feedback information from the admittance model, the control system adjusts the robot's motion to achieve the desired effect. An important advantage of the admittance control method is its adaptability and flexibility.

[0155] Because admittance control adjusts the robot's motion based on real-time feedback, it can cope with changes and uncertainties in the environment, such as encountering obstacles or external disturbances.

[0156] A typical admittance model is shown in formula (4):

[0157]

[0158] in, represents acceleration, Indicates speed, Indicates displacement, m, k d 、k p The model parameters may be pre-set or determined in other ways, and this exemplary embodiment does not impose any special limitation on this.

[0159] In step S620 , a target force is determined according to the second comparison result, the target model, and the tracking controller.

[0160] In an alternative embodiment, Figure 7 A flow chart of another method for further determining the target force is shown in FIG. Figure 7 As shown, the method may include at least the following steps: in step S710, when the second comparison result is that the contact force is greater than the second threshold, a first offset parameter is obtained using the target model.

[0161] When the second comparison result is that the contact force is greater than the second threshold, the admittance control method can calculate a position offset according to the admittance model. as the first offset parameter.

[0162] In step S720, desired pose information is determined according to the first offset parameter, and the tracking controller is updated using the desired pose information.

[0163] Furthermore, according to formula (5), a new desired target position obtained by upward offset along the normal direction of the contact surface is generated as the desired pose information:

[0164]

[0165] Therefore, the tracking controller is updated with the new desired pose information according to formula (6):

[0166]

[0167] In step S730 , a target force is determined according to the updated tracking controller.

[0168] Based on this, when the second comparison result is that the contact force is greater than the second threshold, the target force can be calculated using the updated tracking controller.

[0169] In an alternative embodiment, Figure 8 A flow chart of another method for further determining the target force is shown in FIG. Figure 8 As shown, the method may include at least the following steps: in step S810, when the second comparison result is that the contact force is less than or equal to the second threshold, obtaining a second offset parameter using the target model.

[0170] When the second comparison result is that the contact force is less than or equal to the second threshold, the admittance control method can calculate an offset downward along the normal direction of the contact surface as the second offset parameter according to the admittance model.

[0171] In step S820 , a target force is determined according to the second offset parameter and the tracking controller.

[0172] When the second offset parameter is a downward offset along the normal direction of the contact surface, it indicates that the target position represented by the target posture information transmitted by the visual sensor has not yet reached the contact surface. Therefore, the second offset parameter of the admittance control and the tracking controller can be used to calculate the target force to further drive the robot to reach the target position.

[0173] Therefore, after determining the target force based on the contact force and the tracking controller, the motion of the robot can be controlled according to the target force.

[0174] The following describes in detail the motion control method of the robot in the embodiment of the present disclosure in conjunction with an application scenario.

[0175] Figure 9 A schematic diagram of a robot motion control method in an application scenario is shown, such as Figure 9 As shown, in step S910, it moves to the initial position.

[0176] First, the robot can be moved to an initial position. Generally, the initial position is set near the target object, and can also be set at any position according to actual needs. This exemplary embodiment does not make special restrictions on this.

[0177] The robot may be a robotic arm, a bipedal robot, or a quadrupedal robot, and this exemplary embodiment does not impose any special limitation on this.

[0178] Figure 10 A schematic diagram of the structure of a robot in an application scenario is shown. Figure 10 As shown, the entire robotic arm has 7 degrees of freedom, thus having a higher degree of freedom when implementing end-point tracking to perform tasks in Cartesian space.

[0179] A force sensor with a sensing accuracy of at least 0.1 N (Newton) is located at the end of the robot. To manipulate objects or make contact with them, tools such as grippers or manipulators can be added to the end of the robot.

[0180] Furthermore, to obtain the target position of the target object, a visual sensor can be provided in the scene to sense and detect the surface of the object and analyze and obtain corresponding position and posture information. The target object can be an object that the robot wants to contact or another object related to the robot, and this exemplary embodiment does not specifically limit this.

[0181] In step S920 , the visual sensor data is read.

[0182] In order to obtain the position of the target object, a visual sensor is set in the end-contact scene of the robot. The visual sensor can perceive and detect the surface of the target object, and analyze it to obtain the corresponding position information and posture information as the original posture information.

[0183] Furthermore, the current position information and posture information representing the end of the robot are obtained as the current posture information, which can be obtained through the robot kinematic model and joint angle solution.

[0184] It is worth noting that the current pose information of the robot is the pose information in the robot's base coordinate system, while the original pose information is the pose information in the camera coordinate system.

[0185] The hand-eye calibration technology can convert the original pose information in the camera coordinate system into the pose information in the robot base coordinate system as the target pose information.

[0186] In step S930 , the target point is approached using a tracking controller.

[0187] In order to control the end of the robot to move to the target position represented by the target posture information to make contact, a tracking controller as shown in formula (1) can be designed.

[0188] In step S940, it is determined whether the target position has been reached.

[0189] In step S950 , it is determined whether the pressing force is greater than the expected force.

[0190] When the end of the robot does not reach the target position, further judgment can be made on the pressing force and the expected force.

[0191] In actual use, due to temperature drift and calibration errors, the target pose information obtained by the visual sensor has certain errors. Therefore, only the target force calculated by the tracking controller shown in formula (1) may drive the robot to collide with the contact surface.

[0192] To avoid this situation, the target force can be determined by integrating the sensing results of the force sensor.

[0193] First, the original force acting on the robot is obtained, and the original force is initially mapped to obtain the intermediate force.

[0194] The force sensor at the end of the robot can sense the force conditions in the end coordinate system as the original force.

[0195] In order to obtain the contact force in the direction of the contact surface, the original force applied to the end can be mapped to the base coordinate system to obtain the intermediate force.

[0196] Furthermore, the intermediate force mapped to the base coordinate system can be mapped to the contact surface coordinate system to obtain the contact force.

[0197] Specifically, the contact force mapping process can be expressed by formula (2).

[0198] After the contact force is obtained, the target force can be determined based on the contact force and the tracking controller.

[0199] The contact force is compared with a corresponding first threshold to obtain a first comparison result, wherein the first threshold can be considered as a desired force, and the contact force can be considered as a pressing force.

[0200] To determine a suitable first threshold value for the contact force, engineers can manually drag the robotic arm into contact with the contact surface in teach mode, record the contact force along the z-axis of the contact surface at this time, and set this contact force as the first threshold value for the contact force in the actual control process.

[0201] Similarly, the first threshold along the x-axis or y-axis of the contact surface may also be determined in this manner, and this exemplary embodiment does not impose any special limitation thereto.

[0202] Then, the target force is determined based on the first comparison result and the tracking controller.

[0203] In step S960, stay at the current position.

[0204] When it is detected that the contact force is greater than the set first threshold, in order to ensure that the robot can maintain contact and prevent collision, the expected position of the tracking controller can be set as the current position.

[0205] Therefore, when the contact force is along the z-axis of the contact surface, the tracking controller can be adjusted to the form shown in formula (3).

[0206] When the first comparison result is that the contact force is less than the first threshold, for example, the contact force is along the z-axis of the contact surface, the form of the tracking controller remains unchanged, and the target force can be calculated using the tracking controller.

[0207] It is worth noting that when the contact force is along the x-axis or y-axis of the contact surface, the target force can also be calculated using the tracking controller.

[0208] Based on this, when the first comparison result is that the contact force is greater than or equal to the first threshold, or the contact force is less than the first threshold, the target force can be determined according to the adjusted tracking controller formula (3).

[0209] In actual use, redundant position quantities can be added at the target position along the normal direction of the contact surface to prevent the robotic arm from failing to touch the contact surface.

[0210] The redundant position amount may be set to data that is the same as the error of the force sensor, or may be set to data that is greater than the error of the force sensor, which is not particularly limited in this exemplary embodiment.

[0211] Figure 11 A flow chart of another robot motion control method in an application scenario is shown. Figure 11 As shown, in step S1110, the admittance controller.

[0212] In order to obtain the position of the target object, a visual sensor is set in the end-contact scene of the robot. The visual sensor can perceive and detect the surface of the target object, and analyze it to obtain the corresponding position information and posture information as the original posture information.

[0213] Furthermore, the current position information and posture information representing the end of the robot are obtained as the current posture information, which can be obtained through the robot kinematic model and joint angle solution.

[0214] It is worth noting that the current pose information of the robot is the pose information in the robot's base coordinate system, while the original pose information is the pose information in the camera coordinate system.

[0215] The hand-eye calibration technique can convert the original pose information in the camera coordinate system into the pose information in the robot base coordinate system as the target pose information. The target pose information can be considered as the desired trajectory of the robot.

[0216] In order to control the end of the robot to move to the target position represented by the target posture information to make contact, a tracking controller as shown in formula (1) can be designed.

[0217] However, in actual use, due to temperature drift and calibration errors, the target pose information obtained by the visual sensor has certain errors. Therefore, only the target force calculated by the tracking controller shown in formula (1) may drive the robot to collide with the contact surface.

[0218] To avoid this situation, the target force can be determined by integrating the sensing results of the force sensor.

[0219] The original force acting on the robot is obtained and the initial mapping process is performed on the original force to obtain the intermediate force.

[0220] The force sensor at the end of the robot can sense the force conditions in the end coordinate system as the original force.

[0221] In order to obtain the contact force in the direction of the contact surface, the original force applied to the end can be mapped to the base coordinate system to obtain the intermediate force.

[0222] Furthermore, the intermediate force mapped to the base coordinate system can be mapped to the contact surface coordinate system to obtain the contact force, that is, the interaction force.

[0223] In step S1120, position controller.

[0224] The contact force is compared with the corresponding second threshold to obtain a second comparison result, and an admittance model is obtained. The admittance model can be shown as formula (4).

[0225] The second threshold may be preset.

[0226] When the second comparison result is that the contact force is greater than the second threshold, the first offset parameter is obtained using the target model.

[0227] When the second comparison result is that the contact force is greater than the second threshold, the admittance control method can calculate a position offset according to the admittance model. as the first offset parameter.

[0228] Desired pose information is determined based on the first offset parameter, and the tracking controller is updated using the desired pose information.

[0229] Furthermore, according to formula (5), a new expected target position obtained by upward offset along the normal direction of the contact surface is generated as the expected posture information.

[0230] Therefore, the tracking controller is updated using the new desired pose information according to formula (6).

[0231] The target force, i.e. the joint control force, is determined based on the updated tracking controller.

[0232] Based on this, when the second comparison result is that the contact force is greater than the second threshold, the updated tracking controller can be used to determine the target force.

[0233] When the second comparison result is that the contact force is less than or equal to the second threshold, a second offset parameter is obtained using the target model.

[0234] When the second comparison result is that the contact force is less than or equal to the second threshold, the admittance control method can calculate an offset downward along the normal direction of the contact surface as the second offset parameter according to the admittance model.

[0235] The target force, ie, the joint control force, is determined according to the second offset parameter and the tracking controller.

[0236] When the second offset parameter is a downward offset along the normal direction of the contact surface, it indicates that the target position represented by the target posture information transmitted by the visual sensor has not yet reached the contact surface. Therefore, the second offset parameter of the admittance control and the tracking controller can be used to obtain the target force to further drive the robot to reach the target position.

[0237] In step S1130, the robot and the working environment.

[0238] Therefore, after determining the target force based on the contact force and the tracking controller, the robot can be controlled to move in the working environment according to the target force.

[0239] In actual use, Figure 11 The motion control method of a robot shown has higher robustness because it is applicable regardless of whether the target position information delivered by the vision sensor is far away from the contact surface.

[0240] and Figure 9 Another robot motion control method shown can avoid motor stalling because the robot arm remains in the current position after the contact force reaches the desired value.

[0241] Therefore, in actual use, operators can choose these two methods according to their needs.

[0242] In an exemplary embodiment of the present disclosure, a tracking controller is determined using current and target pose information, and the robot's motion is controlled based on the acquired contact force and the tracking controller, providing a robot motion control method that integrates pose information and force information. On the one hand, there is no need to constantly re-teach the motion trajectory based on changes in target pose information, which improves the generalization and accuracy of the robot's motion control and ensures accurate contact between the robot and the contact surface. On the other hand, the accuracy requirements for the sensors that collect pose and force information are reduced, providing a certain degree of fault tolerance for errors caused by hardware, avoiding collisions and damage to the robot, and improving the robustness of the robot's motion control.

[0243] In addition, in an exemplary embodiment of the present disclosure, a motion control device for a robot is also provided. Figure 12 The schematic diagram of the robot's motion control device is shown in FIG. Figure 12 As shown, the robot motion control device 1200 may include: a posture acquisition module 1210, a force acquisition module 1220 and a fusion control module 1230. Among them:

[0244] The posture acquisition module 1210 is configured to obtain the current posture information of the robot and the target posture information corresponding to the current posture information;

[0245] a force acquisition module 1220 configured to determine a tracking controller according to the current posture information and the target posture information, and acquire the contact force exerted on the robot;

[0246] The fusion control module 1230 is configured to determine a target force according to the contact force and the tracking controller, so as to control the movement of the robot according to the target force.

[0247] In some embodiments of the present disclosure, the posture acquisition module 1210 is configured to:

[0248] Obtaining the current posture information of the robot and the original posture information corresponding to the current posture information;

[0249] The hand-eye calibration technology is used to map the original posture information to obtain the target posture information.

[0250] In some embodiments of the present disclosure, the force acquisition module 1220 is configured to:

[0251] Obtaining the original force exerted on the robot, and performing initial mapping processing on the original force to obtain an intermediate force;

[0252] The intermediate force is subjected to advanced mapping processing to obtain the contact force.

[0253] In some embodiments of the present disclosure, the fusion control module 1230 is configured to:

[0254] Comparing the contact force with a corresponding first threshold to obtain a first comparison result;

[0255] A target force is determined based on the first comparison result and the tracking controller.

[0256] In some embodiments of the present disclosure, the fusion control module 1230 is configured to:

[0257] When the first comparison result is that the contact force is less than the first threshold, determining a target force using the tracking controller;

[0258] When the first comparison result is that the contact force is greater than or equal to the first threshold, a target force is determined according to the current posture information.

[0259] In some embodiments of the present disclosure, the fusion control module 1230 is configured to:

[0260] Comparing the contact force with a corresponding second threshold value to obtain a second comparison result, and acquiring a target model;

[0261] A target force is determined based on the second comparison result, the target model, and the tracking controller.

[0262] In some embodiments of the present disclosure, the fusion control module 1230 is configured to:

[0263] When the second comparison result is that the contact force is greater than the second threshold, obtaining a first offset parameter using the target model;

[0264] Determining desired pose information according to the first offset parameter, and updating the tracking controller using the desired pose information;

[0265] A target force is determined based on the updated tracking controller.

[0266] In some embodiments of the present disclosure, the fusion control module 1230 is configured to:

[0267] When the second comparison result is that the contact force is less than or equal to the second threshold, obtaining a second offset parameter using the target model;

[0268] A target force is determined based on the second offset parameter and the tracking controller.

[0269] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0270] The present disclosure also provides a computer-readable storage medium having computer program instructions stored thereon, which implement the steps of the robot motion control method provided by the present disclosure when the program instructions are executed by a processor.

[0271] Figure 13 FIG1 is a block diagram of another motion control device 1300 for a robot according to an exemplary embodiment. For example, the device 1300 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0272] Reference Figure 13 , the device 1300 may include one or more of the following components: a processing component 1302 , a memory 1304 , a power component 1306 , a multimedia component 1308 , an audio component 1310 , an input / output interface 1312 , a sensor component 1314 , and a communication component 1316 .

[0273] Processing component 1302 generally controls the overall operation of device 1300, such as operations associated with display, phone calls, data communications, camera operation, and recording operations. Processing component 1302 may include one or more processors 1320 to execute instructions to perform all or part of the steps of the above-described methods. In addition, processing component 1302 may include one or more modules to facilitate interaction between processing component 1302 and other components. For example, processing component 1302 may include a multimedia module to facilitate interaction between multimedia component 1308 and processing component 1302.

[0274] The memory 1304 is configured to store various types of data to support the operations of the device 1300. Examples of such data include instructions for any application or method operating on the device 1300, contact data, phone book data, messages, pictures, videos, etc. The memory 1304 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0275] The power supply component 1306 provides power to the various components of the device 1300. The power supply component 1306 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device 1300.

[0276] The multimedia component 1308 includes a screen that provides an output interface between the device 1300 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor can not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 1308 includes a front camera and / or a rear camera. When the device 1300 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have focal length and optical zoom capabilities.

[0277] The audio component 1310 is configured to output and / or input audio signals. For example, the audio component 1310 includes a microphone (MIC) that is configured to receive external audio signals when the device 1300 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 1304 or transmitted via the communication component 1316. In some embodiments, the audio component 1310 further includes a speaker for outputting audio signals.

[0278] The input / output interface 1312 provides an interface between the processing component 1302 and peripheral interface modules, such as a keyboard, a click wheel, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0279] Sensor assembly 1314 includes one or more sensors for providing various aspects of the status assessment of device 1300. For example, sensor assembly 1314 can detect the open / closed state of device 1300, the relative positioning of components, such as the display and keypad of device 1300. Sensor assembly 1314 can also detect changes in the position of device 1300 or a component of device 1300, the presence or absence of user contact with device 1300, the orientation or acceleration / deceleration of device 1300, and changes in the temperature of device 1300. Sensor assembly 1314 can include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 1314 can also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 1314 can also include an accelerometer, a gyroscope, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0280] The communication component 1316 is configured to facilitate wired or wireless communication between the device 1300 and other devices. The device 1300 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 1316 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 1316 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0281] In an exemplary embodiment, the apparatus 1300 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described methods.

[0282] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 1304 including instructions, which can be executed by the processor 1320 of the apparatus 1300 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0283] In addition to being an independent electronic device, the above-mentioned device can also be a part of an independent electronic device. For example, in one embodiment, the device can be an integrated circuit (IC) or a chip, wherein the integrated circuit can be a single IC or a collection of multiple ICs; the chip can include but is not limited to the following types: GPU (Graphics Processing Unit), CPU (Central Processing Unit), FPGA (Field Programmable Gate Array), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), SOC (System on Chip, SoC, system on chip or system-on-chip), etc. The above-mentioned integrated circuit or chip can be used to execute executable instructions (or codes) to implement the above-mentioned robot motion control method. The executable instructions can be stored in the integrated circuit or chip, or can be obtained from other devices or equipment. For example, the integrated circuit or chip includes a processor, a memory, and an interface for communicating with other devices. The executable instruction can be stored in the memory, and when the executable instruction is executed by the processor, the above-mentioned robot motion control method is implemented; alternatively, the integrated circuit or chip can receive the executable instruction through the interface and transmit it to the processor for execution to implement the above-mentioned method.

[0284] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program executable by a programmable device, and has a code portion for executing the above-mentioned robot motion control method when executed by the programmable device.

[0285] Figure 14 FIG. 1 is a block diagram of another motion control device 1400 for a robot according to an exemplary embodiment. For example, the device 1400 may be provided as a server. Figure 14 The apparatus 1400 includes a processing component 1422, which further includes one or more processors and a memory resource represented by a memory 1432 for storing instructions, such as an application, that can be executed by the processing component 1422. The application stored in the memory 1432 can include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1422 is configured to execute the instructions to perform the above-mentioned robot motion control method.

[0286] Device 1400 may also include a power supply component 1426 configured to perform power management of device 1400, a wired or wireless network interface 1450 configured to connect device 1400 to a network, and an input / output interface 1458. Device 1400 may operate based on an operating system stored in memory 1432.

[0287] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the present disclosure. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the following claims.

[0288] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A robot motion control method, characterized in that: include: Obtaining the current posture information of the robot and the target posture information corresponding to the current posture information; Determining a tracking controller according to the current posture information and the target posture information, and obtaining a contact force on the robot; A target force is determined based on the contact force and the tracking controller to control the motion of the robot based on the target force.

2. The robot motion control method according to claim 1, characterized in that: The obtaining of the current posture information of the robot and the target posture information corresponding to the current posture information includes: Obtaining the current posture information of the robot and the original posture information corresponding to the current posture information; The hand-eye calibration technology is used to map the original posture information to obtain the target posture information.

3. The robot motion control method according to claim 1, characterized in that: The obtaining of the contact force applied to the robot comprises: Obtaining the original force exerted on the robot, and performing initial mapping processing on the original force to obtain an intermediate force; The intermediate force is subjected to advanced mapping processing to obtain the contact force.

4. The robot motion control method according to claim 1, characterized in that: The determining of the target force according to the contact force and the tracking controller comprises: Comparing the contact force with a corresponding first threshold to obtain a first comparison result; A target force is determined based on the first comparison result and the tracking controller.

5. The robot motion control method according to claim 4, characterized in that: The determining the target force according to the first comparison result and the tracking controller includes: When the first comparison result is that the contact force is less than the first threshold, determining a target force using the tracking controller; When the first comparison result is that the contact force is greater than or equal to the first threshold, a target force is determined according to the current posture information.

6. The robot motion control method according to claim 1, characterized in that: The determining of the target force according to the contact force and the tracking controller comprises: Comparing the contact force with a corresponding second threshold value to obtain a second comparison result, and acquiring a target model; A target force is determined based on the second comparison result, the target model, and the tracking controller.

7. The robot motion control method according to claim 6, characterized in that: The determining the target force according to the second comparison result, the target model, and the tracking controller includes: When the second comparison result is that the contact force is greater than the second threshold, obtaining a first offset parameter using the target model; Determining desired pose information according to the first offset parameter, and updating the tracking controller using the desired pose information; A target force is determined based on the updated tracking controller.

8. The robot motion control method according to claim 6, characterized in that: The determining the target force according to the second comparison result, the target model, and the tracking controller includes: When the second comparison result is that the contact force is less than or equal to the second threshold, obtaining a second offset parameter using the target model; A target force is determined based on the second offset parameter and the tracking controller.

9. A robot motion control device, characterized in that: include: A posture acquisition module is configured to obtain current posture information of the robot and target posture information corresponding to the current posture information; a force acquisition module, configured to determine a tracking controller according to the current posture information and the target posture information, and acquire the contact force exerted on the robot; A fusion control module is configured to determine a target force according to the contact force and the tracking controller, so as to control the motion of the robot according to the target force.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

11. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 8.

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