Improving Legged Robot Locomotion by Quantifying Morphological Computation

Many robotic and biological systems exploit their morphology’s interaction with the environment to become more adaptable, more energy efficient, and to simplify their control. The principles of morphological computation (MC) have been increasingly studied in recent years and researchers have investigated theoretical approaches to quantify the contribution of MC for a variety of robotic systems using only simulated models. In this work, we quantify MC in a physical robotic system, utilizing position-controlled legs with two degrees of freedom in two designs of different elastic compliance, on a bespoke test rig to execute a walking gait. The contribution of morphology was estimated by applying a theoretical model at various stages within the gait cycle to quantify the MC. The relationships between MC and the ground reaction forces and actuator energy consumption are analyzed. The results indicating that increasing the compliance in the leg morphology increases the mean MC value (7.70±1.49) relative to a traditional leg design (5.03±2.27). Periods of high MC were found to occur during the swing phase of the walking gait and reduced during the stance phase with ground reaction forces, which correlates with the findings of prior theoretical studies of MC in hopping gaits. The benefits of refining the leg morphology for higher MC is demonstrated by the measurements of cost of transport (COT), where the leg with the higher mean MC of 7.70 has a lower mean COT of 102.8 compared to the other leg’s mean COT of 153.8. The results demonstrate how real-world measurements of MC may help design the morphology of improved robotics systems.