A parallel inverse kinematics solution for robot manipulators based on multiprocessing and linear extrapolation

A method of computing inverse kinematics in parallel for robots with a closed-form solution is presented. The computational task of computing each inverse kinematics solution is partitioned with one subtask per joint, and all subtasks are computed concurrently. The intrinsic dependency among subtasks is removed by linear extrapolation through the gradient of inverse kinematic functions and joint velocity information. The high degree of concurrency and naturally balanced concurrent subtasks of the system significantly reduce the latency of the inverse kinematics evaluation. Compared with a serial solution, the algorithm results in a reduction of the time of execution by a factor proportional to the number of joints when implemented on a multiprocessor system. Its simplicity makes it easily applicable to any robot manipulators with closed-form solutions. Examples are used to illustrate the effectiveness and the efficiency of the algorithm. Implementation of the algorithm on a multiprocessor system is also discussed