Generic Development of Bin Pick-and-Place System Based on Robot Operating System
學年 110
學期 2
出版(發表)日期 2022-06-10
作品名稱 Generic Development of Bin Pick-and-Place System Based on Robot Operating System
著者 Ching-Chang Wong; Chi-Yi Tsai; Ren-Jie Chen; Shao-Yu Chien; Yi-He Yang; Shang-Wen Wong; Chun-An Yeh
著錄名稱、卷期、頁數 IEEE Access 10, p. 65257-65270
摘要 Bin pick-and-place is an important topic in factory automation and warehouse automation. In this paper, a bin pick-and-place system based on robot operating system (ROS) is implemented to make a six-degree-of-freedom (6-DOF) robot manipulator to complete multiple pick-and-place tasks. The proposed system uses ROS to integrate an object perception module and a pick-and-place module, where the former uses an RGB-D camera to capture images inside the bin, and the latter controls a 6-DOF robot manipulator and two self-made vacuum tools. To estimate the pose of the target object, a YOLOv4 object detector is implemented, and an object sorting method is proposed to find the target object in the image. Then, a pose estimation method based on computer aided design (CAD) is proposed to estimate the pose of target object. To perform the object pick-and-place operations, a coordinate transformation node is designed to transfer the pose of the target object into the workspace. Then, a link distance-based bin collision avoidance method is proposed to avoid collisions. Finally, the angle of the 1-DOF vacuum tool and the picking and placement poses of the robot manipulator are obtained from the result of the bin collision avoidance and the pose of the target object. In this study, a total of ten ROS nodes are designed, and the solutions that make each function easier to implement and reproduce are proposed. In the experiments, we set up four experiments with two task types and two object types to verify the effectiveness of the implemented bin pick-and-place system.
關鍵字 Robots; Task analysis; Robot kinematics; Manipulators; Collision avoidance; Object detection; Pose estimation
語言 en_US
ISSN 2169-3536
期刊性質 國外
收錄於 SCI EI
國別 USA
出版型式 ,電子版