Ir al contenido

Documat


Cartesian space robot manipulator clamping movement in ROS simulation and experiment

  • Longtao Mu [3] ; Yunfei Zhou [1] ; Tiebiao Zhao [2]
    1. [1] Xi'an University of Finance and Economics

      Xi'an University of Finance and Economics

      China

    2. [2] University of California, Merced

      University of California, Merced

      Estados Unidos

    3. [3] School of Mechanical Engineering, Shaanxi Polytechnic Institute
  • Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 6, Nº. 2, 2021, págs. 43-52
  • Idioma: inglés
  • DOI: 10.2478/amns.2021.1.00011
  • Enlaces
  • Resumen
    • 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.


Fundación Dialnet

Mi Documat

Opciones de artículo

Opciones de compartir

Opciones de entorno