Manipulator System Designs for Drawing Random Objects through Point Cloud Posture Estimation
學年 109
學期 2
出版(發表)日期 2021-03-29
作品名稱 Manipulator System Designs for Drawing Random Objects through Point Cloud Posture Estimation
著者 Ching-Chang Wong; Hsuan.Ming Feng; Yu-Cheng Lai,; Hsiang-Yun Chen
著錄名稱、卷期、頁數 Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture p.1-18
摘要 This paper designed a 7-DOF redundant robot manipulator that can flexibly and efficiently pick-up random objects. The developed 7-DOF machine with an additional redundancy achieved great progress in terms of flexibility and efficiency in the operational space. A robot operating system (ROS) was used to configure the manipulator system’s software modules, supporting convenient system interface, appropriate movement control policy, and powerful hardware device management for better regulation of the manipulator’s motions. A 3D type Point Cloud Library (PCL) was utilized to perform a novel point cloud image pre-processing method that did not only reduce the point cloud number but also maintained the original quality. The results of the experiment showed that the estimation speed in object detection and recognition procedure improved significantly. The redundant robot manipulator architecture with the two-stage search algorithm was able to find the optimal null space. Suitable parameters in D-H transformation of forward kinematics were selected to efficiently control and position the manipulator in the right posture. Meanwhile, the reverse kinematics estimated all angles of the joints through the known manipulator position, orientation, and redundancy. Finally, motion panning implementation of manipulator rapidly and successfully reached the random object position and automatically drew it up to approximate the desired target.
關鍵字 Manipulator system;point cloud;robot operating system;drawing random objects;image segmentation
語言 en_US
期刊性質 國外
收錄於 SCI Scopus
國別 GBR
出版型式 ,電子版

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SDGS 優質教育,產業創新與基礎設施