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

The authors present a method to compute inverse kinematics in parallel for robots with a closed-form solution, and distinguish a pipelined solution from a parallel solution. Although both increase the system throughput, only the parallel solution reduces the computational latency. The computational task of computing inverse kinematics is partitioned with one subtask per joint, and all subtasks are computed in parallel. The intrinsic dependency among subtasks is removed by linear extrapolation through the gradient of the inverse kinematic functions and joint velocity information. The simplicity of the solution makes it easily applicable to any robot manipulator with a closed-form solution. Examples are used to illustrate the effectiveness and efficiency of the algorithm. Implementation of the algorithm on a multiprocessor system is described