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<p>This paper studies the robot arm sorting position control based on robot operation system (ROS), which works depending on the characteristics of the robot arm sorting operation using the top method, to automate the sorting operation and improve the work efficiency of workpiece sorting. Through the ROS MoveIt! module, the sorting pose and movement path of the robotic arm are planned, the inverse kinematics of the sorting robotic arm is solved, and the movement pose characteristics of the sorting robotic arm are analysed. The robot arm model was created using Solidworks software, and the URDF model file of the robot arm was exported through the sw2urdf plugin conversion tool, and the parameters were configured. Based on ROS for 6-degree-of-freedom (DOF) robot motion simulation, random extended tree (RRT) algorithm from open motion planning library (OMPL) is selected. The robot motion planning analysis and sorting manipulator drive UR5 manipulator. The results show that the sorting pose and motion trajectory of the robot arm are determined by controlling the sorting pose of the sorting robot arm, and the maximum radius value of the tool centre point (TCP) rotation of the robot arm and the position of the workpiece are obtained. This method can improve the success rate of industrial sorting robots in grabbing objects. This analysis is of great significance to the research of robots’ autonomous object grabbing.</p>
</abstract>

This paper studies the robot arm sorting position control based on robot operation system (ROS), which works depending on the characteristics of the robot arm sorting operation using the top method, to automate the sorting operation and improve the work efficiency of workpiece sorting. Through the ROS MoveIt! module, the sorting pose and movement path of the robotic arm are planned, the inverse kinematics of the sorting robotic arm is solved, and the movement pose characteristics of the sorting robotic arm are analysed. The robot arm model was created using Solidworks software, and the URDF model file of the robot arm was exported through the sw2urdf plugin conversion tool, and the parameters were configured. Based on ROS for 6-degree-of-freedom (DOF) robot motion simulation, random extended tree (RRT) algorithm from open motion planning library (OMPL) is selected. The robot motion planning analysis and sorting manipulator drive UR5 manipulator. The results show that the sorting pose and motion trajectory of the robot arm are determined by controlling the sorting pose of the sorting robot arm, and the maximum radius value of the tool centre point (TCP) rotation of the robot arm and the position of the workpiece are obtained. This method can improve the success rate of industrial sorting robots in grabbing objects. This analysis is of great significance to the research of robots’ autonomous object grabbing.

Cartesian space robot manipulator clamping movement in ROS simulation and experiment

Xi’an University of Finance and Economics

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper studies the robot arm sorting position control based on robot operation system (ROS), which works depending on the characteristics of the robot arm...

Cartesian space robot manipulator clamping movement in ROS simulation and experiment

Online veröffentlicht: 15. Feb. 2021

Seitenbereich: 43 - 52

Eingereicht: 29. Sept. 2020

Akzeptiert: 30. Nov. 2020

DOI: https://doi.org/10.2478/amns.2021.1.00011

Schlüsselwörter
industrial robot, universal robot, robot operation system, kinematic simulation

© 2020 Longtao Mu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Cartesian space robot manipulator clamping movement in ROS simulation and experiment

Online veröffentlicht: 15. Feb. 2021

Seitenbereich: 43 - 52

Eingereicht: 29. Sept. 2020

Akzeptiert: 30. Nov. 2020

DOI: https://doi.org/10.2478/amns.2021.1.00011

Schlüsselwörterindustrial robot, universal robot, robot operation system, kinematic simulation

© 2020 Longtao Mu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
industrial robot, universal robot, robot operation system, kinematic simulation