CN110497405B - Force feedback man-machine cooperation anti-collision detection method and module for driving and controlling integrated control system - Google Patents
Force feedback man-machine cooperation anti-collision detection method and module for driving and controlling integrated control system Download PDFInfo
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Abstract
The method comprises the steps of S1, establishing a robot dynamic equation on a preset robot platform; s2, constructing a collision detection operator based on the invariance of the robot energy and a disturbance observer based on the generalized momentum variation; s3, determining the relation between the torque and the collision force of each joint based on the real-time feedback of the current of the robot system; s4, based on the detection result of the collision detection model, aiming at different collision situations, making different safety protection strategies; s5, carrying out simulation verification and optimization on the effectiveness of a robot collision detection operator and the rationality of a safety protection strategy based on an ADAMS-Simulink combined simulation platform; and S6, verifying and evaluating the actual effect of the obstacle avoidance and protection safety strategy based on force feedback. The invention has the advantage of collision detection capability on the premise of not increasing the complexity and the overall cost of the system.
Description
Technical Field
The invention belongs to the field of cooperative robots, and particularly relates to a force feedback man-machine cooperation anti-collision detection method and module for a drive-control integrated control system.
Background
Along with the development and progress of the driving and controlling integrated technology, the performance of the industrial robot is obviously improved, the functions are more and more abundant, the environmental adaptability is stronger and stronger, the working efficiency is higher and higher, and the labor force is greatly liberated. However, at present, industrial robots are more suitable for performing some labor-intensive repeated work, and are difficult to be competent for some work requiring priori knowledge and experience accumulation, and a man-machine cooperation working mode can provide an ideal solution. Therefore, the cooperative machines are produced at the same time, and the rapid detection of robot collision and the rapid decision of safety protection under the complex environment of man-machine cooperation are of great importance to guarantee the safety of personnel and the safety of the robot. Because the cooperative robot generally has larger inertia and limited environment perception capability, and the randomness and uncertainty of human work activities, interference and even collision potential safety hazards exist in the human-computer cooperation process, higher requirements are provided for a driving and controlling integrated control system, the driving and controlling integrated control system is required to have certain collision detection capability on the premise of not increasing the complexity and the overall cost of the system, and an optimal safety protection strategy can be adopted according to actual working conditions.
Disclosure of Invention
In order to solve the problems, the invention provides a force feedback man-machine cooperation anti-collision detection method and a module for a driving and controlling integrated control system, which have collision detection capability on the premise of not increasing the complexity and the overall cost of the system.
The technical scheme of the invention is as follows: the force feedback man-machine cooperation anti-collision detection method for the drive and control integrated control system comprises the following steps:
s1, establishing a connecting rod coordinate system on a preset robot platform by adopting a D-H parameter method, and establishing a robot kinetic equation according to a Lagrange kinetic formula;
s2, constructing a collision detection operator based on the unchanged energy of the robot and a disturbance observer based on the variable quantity of the generalized momentum according to a robot dynamic equation and a momentum equation;
s3, determining the relation between the torque and the collision force of each joint based on the real-time feedback of the robot system current, providing a Jacobian matrix solving method for the robot, and analyzing the effectiveness of the detection collision;
s4, based on the detection result of the collision detection model, aiming at different collision situations, combining with actual working conditions, making different safety protection strategies;
s5, carrying out simulation verification and optimization on the effectiveness of a robot collision detection operator and the rationality of a safety protection strategy based on an ADAMS-Simulink combined simulation platform;
and S6, verifying and evaluating the actual effect of the obstacle avoidance and protection safety strategy based on force feedback based on a preset robot platform.
As an improvement to the present invention, the security protection policy includes: (1) stopping after collision, namely immediately enabling the servo driver to be disconnected by the control system after the robot control system detects a collision signal; or (2) the robot control system switches the control mode after collision, and converts the position mode into a torque mode; or (3) after the collision, the robot changes the original motion track and leaves the collision area.
As an improvement to the present invention, before the step S1, the method further includes the following steps:
s11, constructing a monocular double-view stereo matching model based on SVS, optimizing geometric constraint conditions on a loss function, and realizing accurate estimation of the depth of a detection target in a monocular image through a left-right view synthesis process and double-view stereo matching;
s12, performing depth convolution feature extraction by adopting a ResNet model based on the RGB image acquired by the monocular camera;
s13, according to the geometric priori knowledge of human skeleton joints and the correlation among the joints, optimizing the structural design of a two-branch depth convolution neural network to realize the synchronous processing of joint points and the correlation among the joints, wherein one branch carries out human skeleton key point regression in a mode of combining a probability heat map and an offset, one branch detects the joint correlation information of multiple persons in an image, and the two branches are matched to form human skeleton sequence data;
s14, reconstructing a human skeleton image dataset by taking a Microsoft COCO dataset as a basis and combining the characteristics of an industrial man-machine cooperation scene, labeling joint point data by adopting open source alphapos of Shanghai university of transportation, and obtaining an attitude dataset facing the industrial cooperation scene by combining manual adjustment.
The invention also provides a force feedback man-machine cooperation anti-collision detection module for the drive-control integrated control system, which comprises:
the system comprises a dynamic equation establishing module, a connecting rod coordinate system and a robot dynamic equation establishing module, wherein the dynamic equation establishing module is used for establishing a connecting rod coordinate system on a preset robot platform by adopting a D-H parameter method and establishing the robot dynamic equation according to a Lagrange dynamic formula;
the collision detection operator and disturbance observer establishing module is used for constructing a collision detection operator based on the unchanged energy of the robot and a disturbance observer based on the variable quantity of the generalized momentum according to a robot dynamic equation and a momentum equation;
the data analysis module is used for determining the relation between the torque and the collision force of each joint based on the real-time feedback of the current of the robot system, providing a Jacobian matrix solving method for the robot and analyzing the effectiveness of the detection collision;
the safety protection strategy making module is used for making different safety protection strategies according to different collision situations and by combining actual working conditions based on the detection result of the collision detection model;
the simulation verification and optimization module is used for performing simulation verification and optimization on the effectiveness of a robot collision detection operator and the rationality of a safety protection strategy based on an ADAMS-Simulink combined simulation platform;
and the actual effect verification module is used for verifying and evaluating the actual effect of the obstacle avoidance and protection safety strategy based on force feedback based on a preset robot platform.
As an improvement to the present invention, the security protection policy includes: (1) stopping after collision, namely immediately enabling the servo driver to be disconnected by the control system after the robot control system detects a collision signal; or (2) the robot control system switches the control mode after collision, and converts the position mode into a torque mode; or (3) after the collision, the robot changes the original motion track and leaves the collision area.
As an improvement to the present invention, the present invention further comprises:
the monocular binocular stereo matching module is used for constructing a monocular binocular stereo matching model based on SVS, optimizing geometric constraint conditions on a loss function, and realizing accurate estimation of the depth of a detection target in a monocular image through a left-right view synthesis process and binocular stereo matching;
the convolution feature extraction module is used for extracting deep convolution features by adopting a ResNet model based on the RGB images collected by the monocular camera;
the human skeleton key point processing module optimizes the structure design of the double-branch depth convolution neural network according to the geometric priori knowledge of human skeleton joints and the correlation relationship among the joints, realizes the synchronous processing of the joint points and the correlation relationship among the joints, one branch performs human skeleton key point regression in a mode of combining a probability heat map and an offset, and one branch detects the joint correlation information of a plurality of people in an image and forms human skeleton sequence data through bipartite map matching;
the human body skeleton image data processing module is used for reconstructing a human body skeleton image data set by combining the characteristics of an industrial man-machine cooperation scene based on a Microsoft COCO data set, labeling joint point data by adopting open source alphaposition of Shanghai university of traffic, and obtaining an attitude data set facing the industrial cooperation scene by combining manual adjustment.
The invention has the advantage of collision detection capability on the premise of not increasing the complexity and the overall cost of the system.
Drawings
FIG. 1 is a schematic block flow diagram of one embodiment of the method of the present invention.
Fig. 2 is a schematic block diagram of an embodiment of the method of the present invention.
Fig. 3 is a schematic structural diagram of an embodiment of the module of the present invention.
Fig. 4 is a schematic diagram of a refined structure of fig. 3.
Detailed Description
Referring to fig. 1, fig. 1 discloses a force feedback man-machine cooperation anti-collision detection method for a driving and controlling integrated control system,
s1, establishing a connecting rod coordinate system by adopting an improved D-H parameter method on a preset robot platform, and establishing a robot dynamic equation according to a Lagrange dynamic formula;
s2, constructing a collision detection operator based on the unchanged energy of the robot and a disturbance observer based on the variable quantity of the generalized momentum according to a robot dynamic equation and a momentum equation;
s3, determining the relation between the torque and the collision force of each joint based on the real-time feedback of the current of the robot system, providing a Jacobian matrix solving method for the robot, and analyzing the effectiveness of the detection collision;
s4, based on the detection result of the collision detection model, aiming at different collision situations, combining with actual working conditions, making different safety protection strategies, and minimizing adverse effects caused by robot collision;
s5, carrying out simulation verification and optimization on the effectiveness of a robot collision detection operator and the rationality of a safety protection strategy based on an ADAMS-Simulink combined simulation platform;
and S6, verifying and evaluating the actual effect of the obstacle avoidance and protection safety strategy based on force feedback based on the preset robot platform.
In the invention, response strategies after collision between the cooperative robot and the cooperative people in the cooperative process are divided into the following three strategies:
(a) stopping after collision, i.e. the control system immediately disables the servo driver after the robot control system detects a collision signal, which actually acts as if the crash stop button is pressed. The method has the advantages of high response speed and good real-time performance; the device has the defects that impact and pressure generated by collision cannot be unloaded, and certain potential safety hazards exist.
(b) The robot control system switches the control mode after collision, converts the position mode into the torque mode, thereby entering the zero-force mode, the motors of all joints of the robot work in the torque mode at the moment, the torque is used for overcoming the gravity torque and the joint friction torque of the robot, the robot is not easy to fall down to cause danger under the condition that the brake does not work, and the actual effect is similar to that the robot is in the process of dragging the teaching. The robot has the advantages that the robot has certain flexibility at the moment, and the collision force can be unloaded.
(c) After collision, the robot changes the original motion track and leaves the collision area. The intelligent obstacle avoidance system has the advantages that non-stop obstacle avoidance is realized, and the intelligent obstacle avoidance system is more intelligent and beneficial to ensuring the working efficiency; the method has the disadvantages of high requirements on motion trajectory planning and collision risk in the process of switching motion paths.
The man-machine cooperative drive and control integrated controller can be suitable for various robot working environments, a corresponding switching interface is arranged aiming at the collision protection safety strategy, and a protection strategy is recommended to a user according to the space change and the danger level of the working environment.
Referring to fig. 2, in order to further improve the safety performance of human-computer cooperation, the invention can also adopt a non-contact and non-controlled machine vision method to carry out technical researches on 3D human body operation behavior posture detection and human-computer collision avoidance in an industrial scene from an accident source, so as to avoid the occurrence of human-computer collision accidents in advance.
Have advantages such as convenient deployment, with low costs according to the monocular camera, based on binocular depth estimation thought, realize: s11, constructing a monocular double-view stereo matching model based on SVS, optimizing geometric constraint conditions on a loss function, and realizing accurate estimation of the depth of a detection target in a monocular image through a left-right view synthesis process and double-view stereo matching;
s12, performing depth convolution feature extraction by adopting a ResNet model based on RGB images acquired by a monocular camera, and optimizing the structural design of a double-branch depth convolution neural network according to the geometrical priori knowledge of human skeleton joints and the correlation among the joints;
s13, realizing synchronous processing of joint points and joint association relations thereof, wherein one branch performs human skeleton key point regression in a mode of combining a probability heat map and an offset, one branch detects joint association information of multiple persons in an image, and human skeleton sequence data are formed through bipartite graph matching;
s14, reconstructing a human skeleton image dataset aiming at the characteristics of an industrial human-computer cooperation scene on the basis of a Microsoft COCO dataset for ensuring the applicability and the reliability of the model, and meanwhile, adopting open source alphapos of Shanghai university of transportation to label joint point data for reducing the workload of dataset production, and combining manual adjustment to obtain an attitude dataset facing the industrial cooperation scene.
Referring to fig. 3 and 4, the present invention further provides a force feedback human-machine cooperation anti-collision detection module for a drive-control integrated control system, including:
the system comprises a dynamics equation establishing module 1, a connecting rod coordinate system and a robot dynamics equation establishing module, wherein the dynamics equation establishing module is used for establishing a connecting rod coordinate system on a preset robot platform by adopting a D-H parameter method and establishing the robot dynamics equation according to a Lagrange dynamics formula;
the collision detection operator and disturbance observer establishing module 2 is used for constructing a collision detection operator based on the unchanged energy of the robot and a disturbance observer based on the variable quantity of the generalized momentum according to a robot dynamic equation and a momentum equation;
the data analysis module 3 determines the relation between the torque and the collision force of each joint based on the real-time feedback of the current of the robot system, provides a Jacobian matrix solving method for the robot, and analyzes the effectiveness of the detection collision;
the safety protection strategy making module 4 is used for making different safety protection strategies according to different collision situations and by combining actual working conditions based on the detection result of the collision detection model;
the simulation verification and optimization module 5 is used for performing simulation verification and optimization on the effectiveness of a robot collision detection operator and the rationality of a safety protection strategy based on an ADAMS-Simulink combined simulation platform;
and the actual effect verification module 6 is used for verifying and evaluating the actual effect of the obstacle avoidance and protection safety strategy based on force feedback based on a preset robot platform.
As an improvement to the present invention, the present invention further comprises:
the monocular double-view stereo matching module 7 is used for constructing a monocular double-view stereo matching model based on SVS, optimizing geometric constraint conditions on a loss function, and realizing accurate estimation of the depth of a detection target in a monocular image through a left-right view synthesis process and double-view stereo matching;
the convolution feature extraction module 8 is used for extracting deep convolution features by adopting a ResNet model based on the RGB images collected by the monocular camera;
the human skeleton key point processing module 9 is used for optimizing the structural design of a double-branch depth convolution neural network according to the geometric priori knowledge of human skeleton joints and the correlation relationship among the joints, so as to realize the synchronous processing of the joint points and the correlation relationship among the joints, wherein one branch carries out human skeleton key point regression in a mode of combining a probability heat map and an offset, and one branch detects the joint correlation information of a plurality of people in an image and forms human skeleton sequence data through bipartite map matching;
the human body skeleton image data processing module 10 is used for reconstructing a human body skeleton image data set by combining the characteristics of an industrial man-machine cooperation scene based on a Microsoft COCO data set, carrying out joint point data annotation by adopting open source alphaphase of Shanghai university of transportation, and obtaining an attitude data set facing the industrial cooperation scene by combining manual adjustment.
Preferably, in this embodiment, the security protection policy includes: 1. stopping after collision, namely immediately enabling the servo driver to be disconnected by the control system after the robot control system detects a collision signal; or 2, switching the control mode by the robot control system after collision, and converting the position mode into a moment mode; or 3, after the collision, the robot changes the original motion track and leaves the collision area.
Claims (4)
1. A force feedback man-machine cooperation anti-collision detection method for a drive-control integrated control system is characterized by comprising the following steps:
s11, constructing a monocular double-view stereo matching model based on SVS, optimizing geometric constraint conditions on a loss function, and realizing accurate estimation of the depth of a detection target in a monocular image through a left-right view synthesis process and double-view stereo matching;
s12, performing depth convolution feature extraction by adopting a ResNet model based on the RGB image acquired by the monocular camera;
s13, according to the geometric priori knowledge of human skeleton joints and the correlation among the joints, optimizing the structural design of a two-branch depth convolution neural network to realize the synchronous processing of joint points and the correlation among the joints, wherein one branch carries out human skeleton key point regression in a mode of combining a probability heat map and an offset, one branch detects the joint correlation information of multiple persons in an image, and the two branches are matched to form human skeleton sequence data;
s14, reconstructing a human skeleton image dataset by taking a Microsoft COCO dataset as a basis and combining the characteristics of an industrial man-machine cooperation scene, labeling joint point data by adopting open source alphapos of Shanghai university of transportation, and obtaining an attitude dataset facing the industrial cooperation scene by combining manual adjustment;
s1, establishing a connecting rod coordinate system by a D-H parameter method on a preset robot platform, and establishing a robot dynamic equation according to a Lagrange dynamic formula;
s2, constructing a collision detection operator based on the unchanged energy of the robot and a disturbance observer based on the variable quantity of the generalized momentum according to a robot dynamic equation and a momentum equation;
s3, determining the relation between the torque and the collision force of each joint based on the real-time feedback of the current of the robot system, providing a Jacobian matrix solving method for the robot, and analyzing the effectiveness of the detection collision;
s4, based on the detection result of the collision detection model, aiming at different collision situations, combining with actual working conditions, making different safety protection strategies;
s5, carrying out simulation verification and optimization on the effectiveness of a robot collision detection operator and the rationality of a safety protection strategy based on an ADAMS-Simulink combined simulation platform;
and S6, verifying and evaluating the actual effect of the obstacle avoidance and protection safety strategy based on force feedback based on a preset robot platform.
2. The force feedback man-machine cooperation anti-collision detection method for the drive and control integrated control system according to claim 1, wherein: the security protection policy comprises: (1) stopping after collision, namely immediately enabling the servo driver to be disconnected by the control system after the robot control system detects a collision signal; or (2) the robot control system switches the control mode after collision, and converts the position mode into a torque mode; or (3) after the collision, the robot changes the original motion track and leaves the collision area.
3. A force feedback human-computer cooperation anti-collision detection module for a drive-control integrated control system is characterized by comprising:
the monocular binocular stereo matching module (7) is used for constructing a monocular binocular stereo matching model based on SVS, optimizing geometric constraint conditions on a loss function, and realizing accurate estimation of the depth of a detection target in a monocular image through a left-right view synthesis process and binocular stereo matching;
the convolution feature extraction module (8) is used for extracting deep convolution features by adopting a ResNet model based on the RGB images collected by the monocular camera;
the human skeleton key point processing module (9) optimizes the structure design of the double-branch depth convolution neural network according to the geometric priori knowledge of the human skeleton joints and the correlation among the joints, realizes the synchronous processing of the joint points and the correlation among the joints, one branch performs human skeleton key point regression in a mode of combining a probability heat map and an offset, and one branch detects the joint correlation information of a plurality of people in an image and forms human skeleton sequence data through bipartite map matching;
the human body skeleton image data processing module (10) is used for reconstructing a human body skeleton image data set by combining the characteristics of an industrial man-machine cooperation scene on the basis of a Microsoft COCO data set, carrying out joint point data annotation by adopting open source alphaphase of Shanghai university of transportation, and obtaining an attitude data set facing the industrial cooperation scene by combining manual adjustment;
the system comprises a dynamics equation establishing module (1) and a control module, wherein the dynamics equation establishing module is used for establishing a connecting rod coordinate system on a preset robot platform by adopting a D-H parameter method and establishing a robot dynamics equation according to a Lagrange dynamics formula;
the collision detection operator and disturbance observer establishing module (2) is used for constructing a collision detection operator based on the unchanged energy of the robot and a disturbance observer based on the variable quantity of the generalized momentum according to a robot dynamic equation and a momentum equation;
the data analysis module (3) determines the relation between the torque and the collision force of each joint based on the real-time feedback of the current of the robot system, provides a Jacobian matrix solving method for the robot, and analyzes the effectiveness of the detection collision;
the safety protection strategy making module (4) is used for making different safety protection strategies according to different collision situations and by combining actual working conditions based on the detection result of the collision detection model;
the simulation verification and optimization module (5) is used for performing simulation verification and optimization on the effectiveness of a robot collision detection operator and the rationality of a safety protection strategy based on an ADAMS-Simulink combined simulation platform;
and the actual effect verification module (6) is used for verifying and evaluating the actual effect of the obstacle avoidance and protection safety strategy based on force feedback based on a preset robot platform.
4. The force feedback human-computer cooperation anti-collision detection module for the drive and control integrated control system according to claim 3, wherein the safety protection strategy comprises: (1) stopping after collision, namely immediately enabling the servo driver to be disconnected by the control system after the robot control system detects a collision signal; or (2) the robot control system switches the control mode after collision, and converts the position mode into a torque mode; or (3) after the collision, the robot changes the original motion track and leaves the collision area.
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| CN111152264B (en) * | 2020-01-03 | 2021-06-11 | 北京理工大学 | Precision measurement module for detecting collision force and power of cooperative robot |
| CN113021340B (en) * | 2021-03-17 | 2022-07-01 | 华中科技大学鄂州工业技术研究院 | Robot control method, device, equipment and computer readable storage medium |
| CN114750168B (en) * | 2022-06-14 | 2022-09-20 | 苏州上舜精密工业科技有限公司 | Mechanical arm control method and system based on machine vision |
| CN117409517B (en) * | 2023-10-19 | 2024-05-07 | 光谷技术有限公司 | Voice alarm system and method based on video AI behavior analysis |
| CN118514082B (en) * | 2024-07-19 | 2024-09-13 | 帕西尼感知科技(深圳)有限公司 | Self-collision avoidance method and device in dragging process of robot and robot system |
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