(A) study on motor controller and distributed computing for compensation of mechanical impedance of multi-joint robot systems

Abstract

Mechanical impedance compensation is very important for precise human-robot interaction and safety of wearable robots. However, the process requires a large computing power and causes a CPU load on the central controller. As a result, it limits the real-time operation of high-level algorithms such as decision-making and trajectory generation. In this paper, a system architecture that compensates mechanical impedance through a motor controller network instead of a central controller is introduced. To implement the architecture, a dual-core motor controller capable of complex calculations, data acquisition, and signal processing has been developed. In addition, using the characteristic that inverse dynamics calculation is possible recursively based on the Newton-Euler equation, a methodology for solving inverse dynamics through distributed computing on the open chain network structure composed of the developed motor control device is presented. By applying this architecture to an actual robot platform and conducting an experiment, it was confirmed that the mechanical impedance decreased and the CPU load of the central controller was reduced.