Composite robot teaching method, device and equipment and storage medium

Abstract

The invention discloses a composite robot teaching method, device and equipment and a storage medium, and the method comprises the steps: determining a target weight matrix based on a whole body equivalent impedance model and a target teaching mode corresponding to a composite robot, and obtaining a current dragging parameter between the composite robot and an operator; based on the target weight matrix, the current dragging parameter is adjusted, and a target dragging parameter between the composite robot and an operator is obtained; and on the basis of the target dragging parameters and the admittance control mode, a mechanical arm control instruction and a chassis control instruction corresponding to the composite robot are generated, and on the basis of the mechanical arm control instruction and the chassis control instruction, motion control over a mechanical arm and a chassis of the composite robot is conducted. Through the technical scheme of the embodiment of the invention, the mechanical arm and the movable chassis can be dragged and demonstrated at the same time, and the operation process is simplified, so that the demonstration efficiency of the composite robot is greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of robot technology, and in particular to a composite robot teaching method, device, equipment and storage medium. Background Art

[0002] With the increasing requirements for robot intelligence, networking, openness and human-machine friendliness, robot teaching technology is playing an increasingly important role in the field of robotics.

[0003] At present, the traditional teaching method of composite robots usually first drags the mechanical arm of the composite robot to the desired position, and records the trajectory, path points and other information of the mechanical arm during the movement, and then uses other special teaching equipment to set the path of the mobile chassis. However, the traditional teaching method of composite robots cannot realize the dragging teaching of the mechanical arm and the mobile chassis at the same time, the operation process is complicated, and the teaching efficiency is low. Summary of the invention

[0004] The present invention provides a composite robot teaching method, device, equipment and storage medium to achieve simultaneous dragging teaching of a mechanical arm and a mobile chassis, simplify the operation process, and thus greatly improve the teaching efficiency of the composite robot.

[0005] In a first aspect, an embodiment of the present invention provides a composite robot teaching method, comprising:

[0006] Based on the whole-body equivalent impedance model and the target teaching mode corresponding to the composite robot, a target weight matrix is ​​determined, and a current drag parameter between the composite robot and the operator is obtained;

[0007] Based on the target weight matrix, the current dragging parameter is adjusted to obtain the target dragging parameter between the composite robot and the operator;

[0008] Based on the target drag parameter and the admittance control method, the manipulator arm control instructions and chassis control instructions corresponding to the composite robot are generated, and based on the manipulator arm control instructions and the chassis control instructions, the motion of the manipulator arm and chassis of the composite robot is controlled.

[0009] In a second aspect, an embodiment of the present invention further provides a composite robot teaching device, comprising:

[0010] A target matrix determination module is used to determine a target weight matrix based on a whole-body equivalent impedance model and a target teaching mode corresponding to the composite robot, and obtain current drag parameters between the composite robot and the operator;

[0011] a target drag parameter determination module, configured to adjust the current drag parameter based on the target weight matrix to obtain the target drag parameter between the composite robot and the operator;

[0012] The target control instruction generation module is used to generate the manipulator control instructions and chassis control instructions corresponding to the composite robot based on the target drag parameter and the admittance control method, and to control the motion of the manipulator arm and chassis of the composite robot based on the manipulator control instructions and the chassis control instructions.

[0013] In a third aspect, an embodiment of the present invention further provides an electronic device, characterized in that the electronic device comprises: at least one processor; and

[0014] a memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the composite robot teaching method provided by any embodiment of the present invention.

[0016] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to execute the compound robot teaching method provided by any embodiment of the present invention when executed.

[0017] The technical solution of the embodiment of the present invention determines the target weight matrix based on the whole body equivalent impedance model and the target teaching mode corresponding to the composite robot, and obtains the current drag parameters between the composite robot and the operator, so that the teaching mode can be flexibly switched according to the target weight matrix. Based on the target weight matrix, the current drag parameters are adjusted to obtain the target drag parameters between the composite robot and the operator, which can ensure that the robot moves according to the operator's intention, thereby improving the accuracy and consistency of control. Based on the target drag parameters and the admittance control mode, the mechanical arm control instructions and chassis control instructions corresponding to the composite robot are generated, and based on the mechanical arm control instructions and the chassis control instructions, the mechanical arm and chassis of the composite robot are controlled to achieve precise motion control of the mechanical arm and chassis of the composite robot. Through the target weight matrix, the control of the mechanical arm and chassis can be optimized and coordinated, the control accuracy and stability can be improved, and then the mechanical arm control instructions and chassis control instructions can be generated to achieve simultaneous drag teaching of the mechanical arm and the mobile chassis, simplify the operation process, and thus greatly improve the teaching efficiency of the composite robot.

[0018] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 is a flow chart of a composite robot teaching method provided according to Embodiment 1 of the present invention;

[0021] Figure 2 is a schematic diagram of a composite robot teaching process according to Embodiment 1 of the present invention;

[0022] Figure 3 is a flow chart of a composite robot teaching method provided according to Embodiment 2 of the present invention;

[0023] Figure 4 is a structural schematic diagram of a composite robot teaching device provided according to Embodiment 3 of the present invention;

[0024] Figure 5 It is a schematic diagram of the structure of an electronic device for implementing the composite robot teaching method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "target", "current", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] Embodiment 1

[0028] Figure 1 A flowchart of a composite robot teaching method is provided for the first embodiment of the present invention. This embodiment is applicable to the case of dragging and teaching a composite robot. Figure 1 As shown, the method can be performed by a composite robot teaching device, which can be implemented in the form of hardware and / or software, and the composite robot teaching device can be configured in an electronic device. Figure 1 As shown, the method specifically comprises the following steps:

[0029] S110 , based on the whole-body equivalent impedance model corresponding to the composite robot and the target teaching mode, determine the target weight matrix, and obtain the current drag parameter between the composite robot and the operator.

[0030] Among them, the composite robot may refer to a robot system consisting of a robotic arm, an autonomous mobile chassis and a controller. The whole-body equivalent impedance model may refer to a comprehensive model that simultaneously equates the robotic arm and the mobile chassis to a second-order "mass-spring-damper" impedance system. The target teaching mode may refer to the teaching requirements for the composite robot as a whole. The target weight matrix may refer to a matrix generated according to the target teaching mode for adjusting the size of the component of the drag force in the corresponding motion direction of the robotic arm / mobile chassis. The current drag parameter may refer to the drag force and torque applied by the operator on the composite robot at the current moment.

[0031] Specifically, a whole-body equivalent impedance model of the composite robot is established. According to the whole-body equivalent impedance model corresponding to the composite robot, different control targets (such as the robotic arm and chassis) are obtained when teaching the composite robot. According to the target teaching mode, the relative importance of each control target is determined, and a target weight matrix is ​​generated. Based on the sensors installed on the robotic arm, the current drag parameters between the composite robot and the operator are obtained, such as Figure 2It should be noted that the target teaching mode corresponds to the target weight matrix one by one, and by adjusting the target weight matrix, flexible switching of different target teaching modes can be achieved.

[0032] Exemplarily, "determining the target weight matrix based on the whole-body equivalent impedance model and the target teaching mode corresponding to the composite robot" in S110 may include: generating an original weight matrix corresponding to the composite robot based on the whole-body equivalent impedance model corresponding to the composite robot; adjusting the original weight matrix based on the target teaching mode to obtain the target weight matrix.

[0033] The original weight matrix may refer to a matrix that has not been adjusted in the initial stage of constructing the target weight matrix. The weight values ​​in the original weight matrix reflect the relative importance of each target in the initial state.

[0034] Specifically, according to the whole-body equivalent impedance model corresponding to the composite robot, different control targets when teaching the composite robot are obtained, and the original weight matrix corresponding to the composite robot is generated. The importance of each control target in the original weight matrix is ​​determined according to the target teaching mode, and the original weight matrix is ​​adjusted to obtain the target weight matrix, thereby realizing the optimization and coordination of multiple control targets in the composite robot and improving the flexibility of teaching.

[0035] S120. Based on the target weight matrix, adjust the current dragging parameters to obtain the target dragging parameters between the composite robot and the operator.

[0036] The target drag parameter may refer to a drag parameter obtained by weighting the drag forces in various directions in the current drag parameter.

[0037] Specifically, Figure 2 As shown in the figure, based on the target weight matrix, the drag force in the current drag parameter is adjusted, and the adjusted drag force and the corresponding torque are used as the target drag parameter between the composite robot and the operator. By adjusting the current drag parameter to obtain the target drag parameter, it can ensure that the composite robot moves according to the operator's intention, and improve the accuracy and consistency of drag teaching.

[0038] Exemplarily, "based on the target weight matrix, adjusting the current dragging parameters to obtain the target dragging parameters between the compound robot and the operator" in S120 may include: weighting the current dragging parameters based on the target weight matrix to obtain the target dragging parameters between the compound robot and the operator after weighted processing.

[0039] Specifically, based on the target weight matrix, the drag force in the current drag parameter is weighted, and the drag force corresponding to the current drag parameter is multiplied by the target weight matrix to obtain the weighted drag force, and the weighted drag force and the corresponding torque are used as the target drag parameter between the composite robot and the operator. By adjusting the current drag parameter to obtain the target drag parameter, it can be ensured that the composite robot moves according to the target teaching mode.

[0040] S130. Generate a manipulator control instruction and a chassis control instruction corresponding to the composite robot based on the target drag parameter and the admittance control mode, and perform motion control of the manipulator arm and chassis of the composite robot based on the manipulator control instruction and the chassis control instruction.

[0041] Among them, the admittance control method may refer to a robot control method based on force control, which realizes the smooth interaction between the robot and the external environment by adjusting the response of the robot end effector to the external force. For example, the admittance control method may be adaptive admittance control. The manipulator control instruction may refer to an instruction for motion control of the manipulator of the composite robot. The chassis control instruction may refer to an instruction for motion control of the mobile chassis of the composite robot.

[0042] Specifically, Figure 2 As shown, the response of the composite robot under the target drag parameter is determined through the admittance control method (adaptive admittance control), and the manipulator control instructions and chassis control instructions corresponding to the composite robot are generated. For example, the manipulator control instructions may include parameters such as the angle and rotation speed of each joint of the manipulator, and the chassis control instructions may refer to parameters such as the speed and direction of the chassis. The manipulator and chassis control the motion of the composite robot according to the received manipulator control instructions and chassis control instructions. The admittance control method enables the robot to quickly respond and adjust to the target drag parameter, thereby improving the flexibility and safety of the robot.

[0043] The technical solution of the embodiment of the present invention determines the target weight matrix based on the whole body equivalent impedance model and the target teaching mode corresponding to the composite robot, and obtains the current drag parameters between the composite robot and the operator, so that the flexible switching of the teaching mode can be realized according to the target weight matrix. Based on the target weight matrix, the current drag parameters are adjusted to obtain the target drag parameters between the composite robot and the operator, which can ensure that the robot moves according to the operator's intention, and improve the accuracy and consistency of the control. Based on the target drag parameters and the admittance control mode, the mechanical arm control instructions and chassis control instructions corresponding to the composite robot are generated, and based on the mechanical arm control instructions and the chassis control instructions, the mechanical arm and chassis of the composite robot are controlled to achieve precise motion control of the mechanical arm and chassis of the composite robot. Through the target weight matrix, the control of the mechanical arm and chassis can be optimized and coordinated, the control accuracy and stability can be improved, and then the mechanical arm control instructions and the chassis control instructions can be generated to achieve the simultaneous drag teaching of the mechanical arm and the mobile chassis, simplify the operation process, and thus greatly improve the teaching efficiency of the composite robot.

[0044] On the basis of the above scheme, after S130, it also includes: obtaining the changing trend of the current drag force of the composite robot, and adjusting the corresponding impedance coefficient of the composite robot according to the changing trend of the current drag force; or, obtaining the current distance between the obstacles around the composite robot and the composite robot and the current posture of the composite robot, and adjusting the corresponding impedance coefficient of the composite robot according to the current distance, the current posture, the preset distance threshold and the preset posture threshold.

[0045] Among them, the current drag force may refer to the magnitude of the drag force acting on the composite robot at the current moment. The impedance coefficient may refer to a comprehensive parameter determined by impedance parameters such as stiffness and damping. By adjusting the impedance coefficient (such as stiffness, damping, etc.) that meets the robot, the response characteristics and adaptability of the robot to external forces can be changed. The current distance may refer to the distance between the composite robot and the obstacle at the current moment. The current posture may refer to the position and posture of the composite robot in three-dimensional space at the current moment. The preset distance threshold may refer to the preset minimum value of the safe distance between the composite robot and the obstacle. The preset posture threshold may refer to a preset posture for judging the safety status of the composite robot.

[0046] Specifically, the current dragging force of the composite robot is acquired in real time through a force sensor and analyzed to determine the changing trend of the current dragging force, and the impedance coefficient corresponding to the composite robot is adaptively adjusted according to the changing trend of the current dragging force to increase the flexibility of the composite robot and avoid excessive resistance to external drag; or, the current distance between the composite robot and the obstacles around the composite robot and the current posture of the composite robot are collected in real time, and the impedance coefficient corresponding to the composite robot is adjusted according to the current distance, the current posture, the preset distance threshold and the preset posture threshold. For example, when it is detected that the obstacle is too close or the current posture of the composite robot is close to a singular posture, the impedance coefficient is increased to prevent the composite robot from continuing to move and improve safety.

[0047] Exemplarily, adjusting the impedance coefficient corresponding to the composite robot according to the change of the current drag force includes: if the change trend of the current drag force is gradually increasing, reducing the impedance coefficient corresponding to the composite robot; if the change trend of the current drag force is gradually decreasing, increasing the impedance coefficient corresponding to the composite robot.

[0048] Specifically, a force sensor or torque sensor installed on the composite robot is used to collect the current drag force in real time, and determine the change trend of the drag force. If the change trend of the drag force is gradually increasing, the impedance coefficient of the composite robot is reduced, so that when the current drag force is large, the composite robot exhibits lower stiffness and damping, increases compliance, and makes the dragging smoother and more comfortable. For example, when the increase in drag force is detected, an instruction can be sent to the impedance controller to reduce the impedance coefficient value set. If the change trend of the drag force is gradually decreasing, the impedance coefficient of the composite robot is increased, so that when the current drag force is small, the composite robot exhibits higher stiffness and damping, which can improve the stability of the composite robot in static or low-speed motion and prevent jitter or loss of control caused by external disturbances or load changes.

[0049] Exemplarily, the impedance coefficient corresponding to the composite robot is adjusted according to the current distance, the current posture, the preset distance threshold and the preset posture threshold, including: if the current distance is less than the preset distance threshold, then based on the negative correlation between the impedance coefficient and the current distance, the impedance coefficient corresponding to the composite robot is adjusted; if the current posture is between the preset posture threshold and the singular posture, then the posture difference between the current posture and the singular posture is determined, and based on the negative correlation between the impedance coefficient and the posture difference, the impedance coefficient corresponding to the composite robot is adjusted.

[0050] Specifically, the current distance between the monitored composite robot and the obstacle is compared with the preset distance threshold. If the current distance is less than the preset distance threshold, the impedance coefficient is adjusted according to the negative correlation between the impedance coefficient and the current distance. Specifically, as the current distance decreases, the impedance coefficient will increase accordingly to increase the robot's resistance to the drag force and prevent the robot from continuing to move toward the obstacle. The monitored current posture is compared with the preset posture threshold and the singular posture (the robot joint reaches the limit position or approaches the inaccessible area). If the current posture is between the preset posture threshold and the singular posture, the system calculates the posture difference between the current posture and the singular posture. Then, the impedance coefficient is adjusted based on the negative correlation between the impedance coefficient and the posture difference. Specifically, as the posture difference between the current posture and the singular posture decreases (that is, the closer to the singular posture), the impedance coefficient will increase accordingly to prevent the robot from continuing to move toward the singular posture.

[0051] Exemplarily, the original weight matrix and the target weight matrix are determined as follows:

[0052] The whole-body equivalent impedance model of the composite robot is established, and the robotic arm and mobile chassis are equivalent to a second-order "mass-spring-damper" impedance system. The expression is as follows:

[0053]

[0054] Among them, M a ,D a ,K a ∈R 6×6 Represents the mass, damping and stiffness coefficients in the equivalent impedance model of the manipulator; represents the acceleration, velocity and position of the end of the robot; f ext =(f x ,f y ,f z ,m x ,m y ,m z ) T ∈R 6 Represents the external force and torque on the end of the robot arm; M m ,D m ,K m ∈R 3×3 Represents the mass, damping and stiffness coefficients in the equivalent impedance model of the moving chassis; represents the acceleration, velocity and position of the mobile chassis in the global coordinate system; S∈R 9×6 represents the original weight matrix.

[0055] The operator teaches by dragging the robot arm. During this process, the controller needs to obtain the force and torque applied by the operator on the robot arm in real time. The acquisition methods include but are not limited to: 1) direct measurement through the six-dimensional force / torque sensor installed at the end of the robot arm; 2) estimation through the built-in joint torque sensor combined with the robot arm dynamics model.

[0056] Before performing drag teaching, the values ​​of the elements in the original weight matrix S can be set according to the target teaching method actually required, thereby adjusting the size of the component of the drag force in the corresponding motion direction of the robot arm / mobile chassis, and then realizing different teaching modes by setting the original weight matrix.

[0057] For example, if the target teaching mode requires the composite robot to work in the manipulator teaching mode and the chassis remains stationary, S can be set to:

[0058]

[0059] at this time

[0060]

[0061] This indicates that the component of the drag force in the chassis moving direction is 0, that is, the chassis will not actively respond to the external force applied by the operator. Similarly, if the target teaching mode requires the composite robot to work in the chassis teaching mode, then set S to:

[0062]

[0063] at this time

[0064]

[0065] It indicates that the component of the drag force in the direction of movement of the robot arm is 0, that is, the robot arm will not actively respond to the external force applied by the operator.

[0066] Exemplarily, the above dynamic adjustment of the impedance coefficient (adaptive admittance control) is specifically performed as follows:

[0067] Calculate the following adjustment factor (i.e. the influence factor of the impedance factor):

[0068] First adjustment factor:

[0069]

[0070] Where, the subscript i represents the i-th motion direction, F i,0 Indicates the maximum user-set value of the drag force in each direction.

[0071] Second adjustment factor:

[0072]

[0073] Where J represents the Jacobian matrix of the robot and a is an adjustable parameter.

[0074] The third adjustment factor:

[0075]

[0076] Where d represents the distance between the mobile chassis and the obstacle, and b is an adjustable parameter.

[0077] According to the above coefficients, the impedance parameters of the robot arm and the mobile chassis are adaptively adjusted respectively. The calculation method is as follows:

[0078]

[0079] in, They respectively represent the reference values ​​of stiffness and damping coefficient in the i-th motion direction of the robot arm.

[0080]

[0081] in, They respectively represent the reference values ​​of stiffness and damping coefficient in the i-th moving direction of the mobile chassis.

[0082] Embodiment 2

[0083] Figure 3 This is a flow chart of a composite robot teaching method provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment optimizes the step of "generating the mechanical arm control instructions and chassis control instructions corresponding to the composite robot based on the target drag parameter and the admittance control mode". The explanations of the terms that are the same or corresponding to the above embodiments are not repeated here.

[0084] See also Figure 3 Another composite robot teaching method provided in this embodiment specifically includes the following steps:

[0085] S210 , based on the whole-body equivalent impedance model corresponding to the composite robot and the target teaching mode, determine the target weight matrix, and obtain the current drag parameter between the composite robot and the operator.

[0086] S220. Based on the target weight matrix, adjust the current dragging parameters to obtain the target dragging parameters between the composite robot and the operator.

[0087] S230, analyzing the current motion state of the composite robot based on the target drag parameter and the admittance control method, and obtaining response parameter information of the composite robot under the action of the target drag parameter.

[0088] The current motion state may refer to the motion parameters of the composite robot at the current moment, and the motion parameters may include information such as the position, velocity, and acceleration of the composite robot. The response parameter information may refer to the motion parameters (position, velocity, acceleration, etc.) that the composite robot is expected to achieve under the action of the target dragging parameters.

[0089] Specifically, the current motion state of the composite robot is collected in real time by sensors, and the target drag parameters are analyzed according to the admittance control method to determine the motion parameters (such as posture, velocity, acceleration, etc.) that the composite robot is expected to achieve under the target drag parameters in the current motion state, and obtain the response parameter information of the composite robot under the target drag parameters, thereby accurately reflecting the actual response of the composite robot under the target drag parameters.

[0090] S240. Based on the response parameter information of the composite robot under the action of the target dragging parameter, obtain the manipulator arm control instructions and chassis control instructions corresponding to the composite robot, and based on the manipulator arm control instructions and the chassis control instructions, perform motion control of the manipulator arm and chassis of the composite robot.

[0091] Specifically, according to the response parameter information of the composite robot under the action of the target dragging parameter, the kinematic inverse algorithm is used to calculate the position or angle of each joint of the composite robot, and the calculated joint position or angle of each joint of the composite robot is further converted into a motion control instruction, and the corresponding manipulator arm control instructions and chassis control instructions of the composite robot are obtained. Based on the manipulator arm control instructions and the chassis control instructions, the motion of the manipulator arm and chassis of the composite robot is controlled, thereby realizing dragging teaching of the manipulator arm and the mobile chassis at the same time, simplifying the operation process, and greatly improving the teaching efficiency of the composite robot.

[0092] The technical solution of the embodiment of the present invention analyzes the current motion state of the composite robot based on the target drag parameter and the admittance control method, and obtains the response parameter information of the composite robot under the action of the target drag parameter, so that the composite robot can adapt to external forces of different sizes and directions, thereby showing good adaptability under different working environments and task requirements. Based on the response parameter information of the composite robot under the action of the target drag parameter, the mechanical arm control instructions and chassis control instructions corresponding to the composite robot are obtained, which can ensure the robot's rapid response to the target drag parameter. By analyzing the current motion state of the composite robot in real time and generating control instructions based on the admittance control method, it can be ensured that the composite robot moves accurately according to the target drag parameter, reducing deviations and errors.

[0093] Exemplarily, the motion command of the robot arm / chassis is calculated based on the admittance control method, and the calculation method is as follows:

[0094]

[0095] Among them, the symbol represents the pseudo-inverse matrix.

[0096] The motion input value of the robot arm is calculated as follows:

[0097]

[0098] Since the mobile chassis mostly works in speed control mode, its motion input value is calculated as follows:

[0099]

[0100] Among them, the superscript t represents the current sampling time, and Δt represents the sampling period of the controller corresponding to the composite robot.

[0101] Embodiment 3

[0102] Figure 4 This is a schematic diagram of the structure of a composite robot teaching device provided by Embodiment 3 of the present invention. Figure 4 As shown, the device includes: a target matrix determination module 310, a target drag parameter determination module 320 and a target control instruction generation module 330.

[0103] The target matrix determination module 310 is used to determine the target weight matrix based on the whole body equivalent impedance model and the target teaching mode corresponding to the composite robot, and obtain the current drag parameters between the composite robot and the operator;

[0104] A target drag parameter determination module 320 is used to adjust the current drag parameter based on the target weight matrix to obtain the target drag parameter between the composite robot and the operator;

[0105] The target control instruction generation module 330 is used to generate the manipulator control instructions and chassis control instructions corresponding to the composite robot based on the target drag parameters and the admittance control method, and to control the motion of the manipulator arm and chassis of the composite robot based on the manipulator control instructions and the chassis control instructions.

[0106] The technical solution of this embodiment determines the target weight matrix based on the whole body equivalent impedance model and the target teaching mode corresponding to the composite robot, and obtains the current drag parameters between the composite robot and the operator, so that the teaching mode can be flexibly switched according to the target weight matrix. Based on the target weight matrix, the current drag parameters are adjusted to obtain the target drag parameters between the composite robot and the operator, which can ensure that the robot moves according to the operator's intention, thereby improving the accuracy and consistency of control. Based on the target drag parameters and the admittance control mode, the mechanical arm control instructions and chassis control instructions corresponding to the composite robot are generated, and based on the mechanical arm control instructions and the chassis control instructions, the motion control of the mechanical arm and chassis of the composite robot is performed, thereby realizing the precise motion control of the mechanical arm and chassis of the composite robot. Through the target weight matrix, the control of the mechanical arm and chassis can be optimized and coordinated, the control accuracy and stability can be improved, and then the mechanical arm control instructions and chassis control instructions can be generated to realize the drag teaching of the mechanical arm and the mobile chassis at the same time, simplify the operation process, and thus greatly improve the teaching efficiency of the composite robot.

[0107] Optionally, the target matrix determination module 310 is specifically used to: generate an original weight matrix corresponding to the composite robot based on a whole-body equivalent impedance model corresponding to the composite robot; and adjust the original weight matrix based on a target teaching mode to obtain a target weight matrix.

[0108] Optionally, the target drag parameter determination module 320 is specifically used to: perform weighted processing on the current drag parameter based on the target weight matrix to obtain the target drag parameter between the compound robot and the operator after the weighted processing.

[0109] Optionally, the target control instruction generation module 330 is specifically used to: analyze the current motion state of the composite robot based on the target drag parameter and the admittance control method, and obtain the response parameter information of the composite robot under the action of the target drag parameter; based on the response parameter information of the composite robot under the action of the target drag parameter, obtain the corresponding manipulator arm control instructions and chassis control instructions of the composite robot.

[0110] Optionally, the above device further includes an impedance coefficient adjustment module.

[0111] The impedance coefficient adjustment module comprises:

[0112] A first adjustment unit is used to obtain a change trend of a current drag force of the composite robot, and adjust an impedance coefficient corresponding to the composite robot according to the change trend of the current drag force; or

[0113] The second adjustment unit is used to obtain the current distance between the obstacles around the composite robot and the composite robot and the current posture of the composite robot, and adjust the impedance coefficient corresponding to the composite robot according to the current distance, the current posture, the preset distance threshold and the preset posture threshold.

[0114] Optionally, the first adjustment unit is specifically used to: if the current drag force has a changing trend of gradually increasing, then reduce the impedance coefficient corresponding to the composite robot; if the current drag force has a changing trend of gradually decreasing, then increase the impedance coefficient corresponding to the composite robot.

[0115] Optionally, the second adjustment unit is specifically used to: if the current distance is less than a preset distance threshold, adjust the impedance coefficient corresponding to the compound robot based on the negative correlation between the impedance coefficient and the current distance; if the current posture is between the preset posture threshold and the singular posture, determine the posture difference between the current posture and the singular posture, and adjust the impedance coefficient corresponding to the compound robot based on the negative correlation between the impedance coefficient and the posture difference.

[0116] The composite robot teaching device provided in the embodiment of the present invention can execute the composite robot teaching method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0117] Figure 5 A schematic diagram of the structure of an electronic device 12 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as desktop computers, workstations, servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0118] like Figure 5 As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0119] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0120] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0121] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 5 not shown, usually called a "hard drive"). Although Figure 5 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0122] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0123] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may communicate with one or more devices that enable a user to interact with the electronic device 12, and / or may communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0124] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing a compound robot teaching method provided in an embodiment of the present invention, the method comprising:

[0125] Based on the whole-body equivalent impedance model and the target teaching mode corresponding to the composite robot, a target weight matrix is ​​determined, and a current drag parameter between the composite robot and the operator is obtained;

[0126] Based on the target weight matrix, the current dragging parameter is adjusted to obtain the target dragging parameter between the composite robot and the operator;

[0127] Based on the target drag parameter and the admittance control method, the manipulator arm control instructions and chassis control instructions corresponding to the composite robot are generated, and based on the manipulator arm control instructions and the chassis control instructions, the motion of the manipulator arm and chassis of the composite robot is controlled.

[0128] Of course, those skilled in the art can understand that the processor can also implement the technical solution consistent with the robot teaching method provided by any embodiment of the present invention.

[0129] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the compound robot teaching method provided in any embodiment of the present invention are implemented. The method includes:

[0130] Based on the whole-body equivalent impedance model and the target teaching mode corresponding to the composite robot, a target weight matrix is ​​determined, and a current drag parameter between the composite robot and the operator is obtained;

[0131] Based on the target weight matrix, the current dragging parameter is adjusted to obtain the target dragging parameter between the composite robot and the operator;

[0132] Based on the target drag parameter and the admittance control method, the manipulator arm control instructions and chassis control instructions corresponding to the composite robot are generated, and based on the manipulator arm control instructions and the chassis control instructions, the motion of the manipulator arm and chassis of the composite robot is controlled.

[0133] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0134] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0135] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0136] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0137] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0138] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A composite robot teaching method, It is characterized in that include: Based on the whole-body equivalent impedance model and the target teaching mode corresponding to the composite robot, a target weight matrix is ​​determined, and a current drag parameter between the composite robot and the operator is obtained; Based on the target weight matrix, the current dragging parameter is adjusted to obtain the target dragging parameter between the composite robot and the operator; Based on the target drag parameter and the admittance control method, the manipulator arm control instructions and chassis control instructions corresponding to the composite robot are generated, and based on the manipulator arm control instructions and the chassis control instructions, the motion of the manipulator arm and chassis of the composite robot is controlled.

2. The method according to claim 1, It is characterized in that The method of determining the target weight matrix based on the whole body equivalent impedance model and the target teaching mode corresponding to the composite robot includes: Based on a whole-body equivalent impedance model corresponding to the composite robot, generating an original weight matrix corresponding to the composite robot; The original weight matrix is ​​adjusted based on the target teaching mode to obtain a target weight matrix.

3. The method according to claim 1, It is characterized in that The step of adjusting the current dragging parameter based on the target weight matrix to obtain the target dragging parameter between the compound robot and the operator includes: The current dragging parameters are weighted based on the target weight matrix to obtain the target dragging parameters between the composite robot and the operator after the weighted processing.

4. The method according to claim 1, It is characterized in that The generating of the manipulator control instructions and chassis control instructions corresponding to the composite robot based on the target drag parameter and the admittance control mode includes: Analyzing the current motion state of the composite robot based on the target drag parameter and the admittance control mode, and obtaining response parameter information of the composite robot under the action of the target drag parameter; Based on the response parameter information of the composite robot under the action of the target drag parameter, a mechanical arm control instruction and a chassis control instruction corresponding to the composite robot are obtained.

5. The method according to claim 1, It is characterized in that After the motion control of the manipulator arm and the chassis of the composite robot is performed based on the manipulator arm control instruction and the chassis control instruction, the method further includes: Obtaining a change trend of the current drag force of the composite robot, and adjusting an impedance coefficient corresponding to the composite robot according to the change trend of the current drag force; or, The current distance between the compound robot and the obstacles around the compound robot and the current posture of the compound robot are obtained, and the impedance coefficient corresponding to the compound robot is adjusted according to the current distance, the current posture, the preset distance threshold and the preset posture threshold.

6. The method according to claim 5, It is characterized in that The adjusting the impedance coefficient corresponding to the composite robot according to the change of the current drag force includes: If the current drag force has a changing trend of gradually increasing, reducing the impedance coefficient corresponding to the composite robot; If the current drag force has a changing trend of gradually decreasing, the impedance coefficient corresponding to the composite robot is increased.

7. The method according to claim 5, It is characterized in that The step of adjusting the impedance coefficient corresponding to the composite robot according to the current distance, the current posture, the preset distance threshold and the preset posture threshold comprises: If the current distance is less than a preset distance threshold, adjusting the impedance coefficient corresponding to the composite robot based on a negative correlation between the impedance coefficient and the current distance; If the current posture is between the preset posture threshold and the singular posture, the posture difference between the current posture and the singular posture is determined, and based on the negative correlation between the impedance coefficient and the posture difference, the impedance coefficient corresponding to the composite robot is adjusted.

8. A composite robot teaching device, It is characterized in that include: A target matrix determination module is used to determine a target weight matrix based on a whole-body equivalent impedance model and a target teaching mode corresponding to the composite robot, and obtain current drag parameters between the composite robot and the operator; a target drag parameter determination module, configured to adjust the current drag parameter based on the target weight matrix to obtain the target drag parameter between the composite robot and the operator; The target control instruction generation module is used to generate the manipulator control instructions and chassis control instructions corresponding to the composite robot based on the target drag parameter and the admittance control method, and to control the motion of the manipulator arm and chassis of the composite robot based on the manipulator control instructions and the chassis control instructions.

9. An electronic device, It is characterized in that The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the compound robot teaching method according to any one of claims 1 to 7.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the compound robot teaching method according to any one of claims 1 to 7 when executed.

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