TY - JOUR
T1 - Path Planning with Automatic Seam Extraction over Point Cloud Models for Robotic Arc Welding
AU - Zhou, Peng
AU - Peng, Rui
AU - Xu, Xinrui
AU - Wu, Victor W.H.
AU - Navarro-Alarcon, David
N1 - Funding Information:
Manuscript received November 23, 2020; accepted March 25, 2021. Date of publication April 2, 2021; date of current version April 20, 2021. This letter was recommended for publication by Associate Editor Y. Joo and Y. Choi upon evaluation of the reviewers’ comments. This work was supported in part by the Research Grants Council under Grant 14203917, in part by the Chinese National Engineering Research Centre for Steel Construction Hong Kong Branch under Grant BBV8, in part by the Key-Area Research and Development Program of Guangdong Province 2020 (project 76), and in part by PolyU under Grants YBYT and ZZHJ. (Corresponding author: David Navarro-Alarcon.) Peng Zhou, Maggie Xu, Victor Wu, and David Navarro-Alarcon are with the Department of Mechanical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong (e-mail: [email protected]; [email protected]; [email protected]; [email protected]).
Publisher Copyright:
© 2021 Tsinghua University Press. All rights reserved.
PY - 2021/7
Y1 - 2021/7
N2 - This letter presents a point cloud based robotic system for arc welding. Using hand gesture controls, the system scans partial point cloud views of workpiece and reconstructs them into a complete 3D model by a linear iterative closest point algorithm. Then, a bilateral filter is extended to denoise the workpiece model and preserve important geometrical information. To extract the welding seam from the model, a novel intensity-based algorithm is proposed that detects edge points and generates a smooth 6-DOF welding path. The methods are tested on multiple workpieces with different joint types and poses. Experimental results prove the robustness and efficiency of this robotic system on automatic path planning for welding applications.
AB - This letter presents a point cloud based robotic system for arc welding. Using hand gesture controls, the system scans partial point cloud views of workpiece and reconstructs them into a complete 3D model by a linear iterative closest point algorithm. Then, a bilateral filter is extended to denoise the workpiece model and preserve important geometrical information. To extract the welding seam from the model, a novel intensity-based algorithm is proposed that detects edge points and generates a smooth 6-DOF welding path. The methods are tested on multiple workpieces with different joint types and poses. Experimental results prove the robustness and efficiency of this robotic system on automatic path planning for welding applications.
KW - Industrial robots
KW - RGB-D perception
KW - motion and path planning
UR - http://www.scopus.com/inward/record.url?scp=85103771951&partnerID=8YFLogxK
U2 - 10.1109/LRA.2021.3070828
DO - 10.1109/LRA.2021.3070828
M3 - Journal article
AN - SCOPUS:85103771951
SN - 2377-3766
VL - 6
SP - 5002
EP - 5009
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 3
M1 - 9394722
ER -