Towards Realization of Legged Robot Capable of Adaptive Running

Abstract

Quadrupeds exhibit versatile gait patterns according to locomotion speed and environment. In particular, they exhibit jumping motion during high-speed running. To investigate how the gait patterns and jumping motion are generated, various intraspinal neural network model have been proposed. However, high-speed running on uneven terrain was not realized. To address the problem, we focused on the vertical velocity of the body parts and designed a new leg-control model that realizes jump by considering leg control during the swing phase. As simulation results, we succeeded in widening the range of locomotion speed and running on uneven terrain. In this study, we developed a one-legged hopping robot and verified the proposed model in the real world.