Inverse Kinematics Of Redundant Robots Using Genetic Algorithms

Transcript

The inverse kinematic solution for redundant robots is much more difficult than for conventional robots. The extremely large number of feasible solutions for most end-effector positions requires additional constraints for proper selection. A genetic algorithm (GA) is presented in this paper which allows additional constraints to be specified easily. The GA is applied to a test problem in which the maximum joint displacement in a point-to-point positioning task is minimized.