Highly parallelized control programming methodologies using multicore CPU and FPGA for highly dynamic multi-DoF mobile robots, applied to the MIT Cheetah

Abstract

This thesis presents highly parallelized control programming methodologies developed for multi-degrees of freedom (DoF) robots capable of highly dynamic movements. In robotic applications that require rapid physical interactions with the environment, it is critical for the robot to achieve a high-frequency synchronization of data processing from a large number of high-bandwidth actuators and sensors. To solve this important problem in robotics, I developed parallelized control programming methodologies that effectively utilize the advantages of modern parallel real-time computing technologies: multicore CPU, the Field Programmable Gate Array (FPGA), and distributed local processors. This approach was implemented in the fast running experiments of the MIT Cheetah. In such a highly dynamic robot, the required control bandwidth is particularly high since the MIT Cheetah's leg actuation system is designed to generate high force (output torque up to 100Nm) with high bandwidth (closed loop bandwidth up to 120Hz) with minimal mechanical impedance for fast locomotive capability. On the integrated control system, a multi-layered architecture is programmed. Inspired by data parallelism, task parallelism, and the pipelining method, more than 50 processes are operated in parallel, and major processes among them are optimized to achieve the maximum throughput.The proposed methodologies enable the high-level control sampling frequency 4 kHz. With this control system platform, I achieved a high-force proprioceptive impedance control [1], and a trot-running up to 6 m/s with a locomotion efficiency rivaling animals [2]..