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Robotic controllers have to execute various complex independent tasks repeatedly. Massive processing power is required by the motion controllers to compute the solution of these computationally intensive algorithms. General-purpose graphics processing unit (GPGPU)-enabled mobile phones can be leveraged for acceleration of these motion controllers. Embedded GPUs can replace several dedicated computing boards by a single powerful and less power-consuming GPU. In this paper, the inverse kinematic algorithm based numeric controllers is proposed and realized using the GPGPU of a handheld mobile device. This work is the extension of a desktop GPU-accelerated robotic controller presented at DAS’16 where the comparative analysis of different sequential and concurrent controllers is discussed. First of all, the inverse kinematic algorithm is sequentially realized using Arduino-Due microcontroller and the field-programmable gate array (FPGA) is used for its parallel implementation. Execution speeds of these controllers are compared with two different GPGPU architectures (Nvidia Quadro K2200 and Nvidia Shield K1 Tablet), programmed with Compute Unified Device Architecture (CUDA) computing language. Experimental data shows that the proposed mobile platform-based scheme outperforms the FPGA by 5× and boasts a 100× speedup over the Arduino-based sequential implementation.