Design and Hardware Implementation of Intelligent Perception Controller for Generic Embedded Robotic Computing Platform

Intelligent robots require extensive robot/human interaction, robot/environment interactions with numerous sensors and actuators, thus, typical robotic computing platforms require a significant amount of computational effort to drive, control, monitor, and data fusion of these devices, at the expense of power consumption. The project will design an intelligent perception controller of robot to offload the computational burden from the host processor of the robotic embedded computing platform, improve real-time performance, and reduce system power consumption. We will design and implement the multi-sensors controller, machine learning based sensor fusion controller, device management engine, and instruction interface controller. Finally, we will realize the HW/SW integration verification of intelligent perception controller with four kinds of robot platforms: wheel-type robot, humanoid robot, six-axis robotic arm and hexapod robot, for demonstrating the real-time performance and power consumption reduction.