Motion Planning for Redundant Manipulators Using a Floating Point Genetic Algorithm

Authors:
Lianfang Tian;Curtis Collins
Affiliations:
Department of Mechanical Engineering, University of California at Riverside, Riverside, CA 92521, U.S.A.;Department of Mechanical Engineering, University of California at Riverside, Riverside, CA 92521, U.S.A./ e-mail: clc@engr.ucr.edu
Venue:
Journal of Intelligent and Robotic Systems
Year:
2003

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Abstract

This paper deals with the trajectory planning problem for redundant manipulators. A genetic algorithm (GA) using a floating point representation is proposed to search for the optimal end-effector trajectory for a redundant manipulator. An evaluation function is defined based on multiple criteria, including the total displacement of the end-effector, the total angular displacement of all the joints, as well as the uniformity of Cartesian and joint space velocities. These criteria result in minimized, smooth end-effector motions. Simulations are carried out for path planning in free space and in a workspace with obstacles. Results demonstrate the effectiveness and capability of the proposed method in generating optimized collision-free trajectories.