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Evolutionary Optimal Trajectory Planning of an Industrial Robot in the Presence of Moving Obstacles
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This paper presents a new general method fo r computing the optimal motions of industrial robot manipulators in the presence of fixed and moving obstacles. The mathematical model considers the nonlinear manipulator dynamics, actuator constraints, joint limits and obstacle avoidance. The problem considered has 5 objective functions, 88 variables and 21 constraints. Two evolutionary algorithms such as Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and Differential Evolution (DE) techniques have been used for the optimization. Given the initial and final configurations, the trajectory is defined using B-spline function and is obtained through off-line computation for on-line operation. The obstacles are considered as objects sharing the same workspace performed by the robot. The obstacle avoidance is expressed in terms of the distances between potentially colliding parts and the motion is represented using translation and rotational matrices. Numerical application involving an industrial manipulator (Adeptone XL robot) is presented. The results obtained from NSGA-II and DE are compared and analyzed. A comprehensive user-friendly general-purpose software package has been developed for the DE algorithm using VC++ to obtain the optimal solutions.
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