A method for robot placement optimization based on two-dimensional manifold in joint space. (February 2021)

• Record Type: Journal Article
• Authors: Li, Guanhua; Zhu, Weidong; Dong, Huiyue; Ke, Yinglin
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 67(2021)
• Publication Date: 2021-02
• Subjects: Robotic machining -- Industrial robot -- Placement -- Manifold -- Error compensation; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2020.102002
• Languages: English
• ISSNs: 0736-5845

Abstract

Highlights: A new method for robot placement optimization is proposed to improve the efficiency of two-dimensional error compensation. The bifurcations which exist in two-dimensional manifolds are clearly explained with the kinematic model. A quantitative index combined with Particle Swarm Optimization (PSO) is proposed to access the two-dimensional manifold. The feasibility of proposed method is validated by positioning error experiments conducted on a typical industrial robot. The whole process of placement optimization can be performed with the help of the integrated controlling system quickly. Abstract: This article addresses a method for placement determination of robotic drilling system on two-dimensional manifold in robot joint space. It has been proved that the feasibility of positioning error compensation on two-dimensional manifold, and that the continuity of the robot parameters in the two-dimensional space is the prerequisite to perform the compensation in previous study. It appears that there are bifurcations which might break the continuity of the robot parameters on the two-dimensional manifold due to improper placement. To avoid bifurcations, a performance index and a set of optimization procedure are proposed to achieve proper placement of robotic machining system. Experiments conducted on a KUKA robot have verified the effectiveness of the proposed placement optimization method. Experiment results indicated that positioning errors were significantly improved with the proposed method, which is beneficial for robotic machining accuracy.