Comparison of GPGPU based robotic manipulator with other embedded controllers

Abstract

Industrial and robotic controllers have to execute various complex independent tasks repeatedly in real time. In order to implement these algorithms with non-linear equations, massive computational power is required in a motion control system. In this paper, inverse kinematics algorithm is selected as a test algorithm to compare performance of General Purpose Graphics Processing Unit (GPGPU) with other widely used sequential and concurrent controllers. Inverse Kinematics algorithm is implemented sequentially in Arduino Due microcontroller and FPGA is used for concurrent implementation where algorithm is designed in VHDL using combinational division. Execution speeds of these controllers are compared with NVIDIA Quadro K2200 GPU programmed with CUDA Parallel Computing Architecture. Results validated that using computational power of GPU, execution time of large independent tasks is significantly decreased.