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A genetic algorithm based strategy for redundancy resolution with multiple criteria

Redundancy of a serial manipulator means that more joints than necessary are available in order to achieve a specified task of the manipulator end-effector. Manipulators are thus allowed to achieve complex tasks by taking into account additional constraints. This paper presents a genetic algorithm based strategy for redundancy resolution with two performance criteria accomplishment, while the end-effector achieves a number of prescribed configurations. The additional constraints added to the main end-effector task are obstacle avoidance and minimization of the sum of joint displacements. The strategy variables are the manipulator base location and the joint configuration adequate to every prescribed end-effector configuration. The strategy is realized using Matlab program with genetic algorithm tool and the illustrative simulations are obtained for a planar redundant manipulator with four degrees of freedom that achieve five different end-effector configurations, while the two performance criteria are accomplished.