Fuzzy inverse kinematic mapping: rule generation, efficiency, and implementation

Abstract

Inverse kinematics is computationally expensive and can result in significant control delays in real time. For a redundant robot, additional computations are required for the inverse kinematic solution through optimization schemes. Based on the fact that humans do not compute exact inverse kinematics, but can do precise positioning for heuristics, an inverse kinematic mapping using fuzzy logic is developed. The implementation of the scheme has demonstrated that it is feasible for both redundant and nonredundant cases, and that it is very computationally efficient. The result provides sufficient precision, and transient tracking error can be controlled based on a fuzzy adaptive scheme proposed in the paper.