TY - GEN
T1 - Robotic Arm Intelligent Grasping System for Garbage Recycling
AU - Fu, Hongyang
AU - Xu, Dong
AU - Wu, Jiang
N1 - Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - The recycling of garbage is an effective way to protect environment. However, garbage recycling is still adopting manual sorting which is of low efficiency and may damage to the health of operators. To improve the efficiency of the garbage recycling, it is considered to use an automated robot system which integrates modern control method of robots and machine vision to replace manual sorting. Using a robotic arm and a RGB-D camera, a visual servo robotic arm grasping system was produced, which mainly depends on tools in robot operating system (ROS). The object recognition kitchen (ORK) in ROS is used to identify and locate the grasping targets. The relationship between the camera coordinate system and the robot coordinate system is established by hand-eye calibration technology. The kinematics calculation and motion planning of the robotic arm are completed with the help of ROS-Moveit!. Through experimental testing, it is estimated that the hand-eye calibration is accurate, and the robotic arm can perfectly grasp the target object.
AB - The recycling of garbage is an effective way to protect environment. However, garbage recycling is still adopting manual sorting which is of low efficiency and may damage to the health of operators. To improve the efficiency of the garbage recycling, it is considered to use an automated robot system which integrates modern control method of robots and machine vision to replace manual sorting. Using a robotic arm and a RGB-D camera, a visual servo robotic arm grasping system was produced, which mainly depends on tools in robot operating system (ROS). The object recognition kitchen (ORK) in ROS is used to identify and locate the grasping targets. The relationship between the camera coordinate system and the robot coordinate system is established by hand-eye calibration technology. The kinematics calculation and motion planning of the robotic arm are completed with the help of ROS-Moveit!. Through experimental testing, it is estimated that the hand-eye calibration is accurate, and the robotic arm can perfectly grasp the target object.
KW - Robot Operating System
KW - hand-eye calibration
KW - motion planning
KW - visual positioning
UR - https://www.scopus.com/pages/publications/85128043223
U2 - 10.1109/CAC53003.2021.9728547
DO - 10.1109/CAC53003.2021.9728547
M3 - 会议稿件
AN - SCOPUS:85128043223
T3 - Proceeding - 2021 China Automation Congress, CAC 2021
SP - 6821
EP - 6826
BT - Proceeding - 2021 China Automation Congress, CAC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 China Automation Congress, CAC 2021
Y2 - 22 October 2021 through 24 October 2021
ER -