Exploiting Dynamical Complexity in a Physical Tensegrity Robot to Achieve Locomotion

Abstract

The emerging field of morphological computation seeks to understand how mechanical complexity in living systems can be advantageous, for instance by reducing the cost of con-trol. In this paper we explore the phenomenon of morpho-logical computation in tensegrities – unique structures with a high strength to weight ratio, resilience, and an ability to change shape. These features have great value as a robotics platform, but also make tensegrities difficult to control via conventional techniques. We describe a novel approach to the control of tensegrity robots which, rather than suppress-ing complex dynamics, exploits them in order to achieve lo-comotion. Our robots are physically embodied (rather than simulated), evolvable, and locomote at higher speeds (relative to body size) and with fewer actuators than those controlled by more conventional approaches.