An optimized adaptive fuzzy inverse kinematics solution for redundant manipulators

Inverse kinematics is computationally expensive and can result in significant control delays in real time. For redundant robots, since there is infinite inverse kinematics solutions, additional computations are required through optimization schemes. Based on the fact that humans do not compute exact inverse kinematics, but can do precise positioning from heuristics, we developed an inverse kinematics solving method through fuzzy logic which is optimized for real time applications. As a result, a simple accurate and fast inverse kinematics solution is obtained. The simulation results verify the efficiency of the proposed solution.