Evolutionary trajectory planning for an industrial robot

Authors:
R. Saravanan;S. Ramabalan;C. Balamurugan;A. Subash
Affiliations:
Department of Mechanical Engineering, Bannariamman Institute of Technology, Sathiamangalam, India 638401;Department of Mechanical Engineering, J. J. College of Engineering and Technology, Thiruchirapalli, India 620009;Department of Production Engineering, J. J. College of Engineering and Technology, Thiruchirapalli, India 620009;Department of Mechanical Engineering, J. J. College of Engineering and Technology, Thiruchirapalli, India 620009
Venue:
International Journal of Automation and Computing
Year:
2010

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Abstract

This paper presents a novel general method for computing optimal motions of an industrial robot manipulator (AdeptOne XL robot) in the presence of fixed and oscillating obstacles. The optimization model considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacle avoidance. The problem has 6 objective functions, 88 variables, and 21 constraints. Two evolutionary algorithms, namely, elitist non-dominated sorting genetic algorithm (NSGA-II) and multi-objective differential evolution (MODE), have been used for the optimization. Two methods (normalized weighting objective functions and average fitness factor) are used to select the best solution tradeoffs. Two multi-objective performance measures, namely solution spread measure and ratio of non-dominated individuals, are used to evaluate the Pareto optimal fronts. Two multi-objective performance measures, namely, optimizer overhead and algorithm effort, are used to find the computational effort of the optimization algorithm. The trajectories are defined by B-spline functions. The results obtained from NSGA-II and MODE are compared and analyzed.