Deep Reinforcement Learning on Passive Walking in Real Environment

Abstract

In this study, we aim to continuous 3 days passive walking. Even if the passive walking robot walks in the same way, it has good or bad condition, and a fall happens unexpectedly. We think that it is possible to avoid fall risk by adjusting the physical parameters of passive walking and keeping good condition. In this paper, we report the adjustment system of passive walking parameters using deep reinforcement learning.