Torso height optimization for bipedal locomotion

Bayesian Gait Optimization for Bipedal Locomotion

One of the key challenges in robotic bipedal locomotion is finding gait parameters that optimize a desired performance metric, such as robustness or energy efficiency. Typically, gait optimization requires extensive robot experiments and specific expert knowledge. Instead, we propose to apply data-driven machine learning to automate and speed up the process of gait optimization. In particular, ...

Gait Regulation for Bipedal Locomotion

This work explores regulation of forward speed, step length, and slope walking for the passive-dynamic class of bipedal robots. Previously, an energy-shaping control for regulating forward speed has appeared in the literature; here we show that control to be a special case of a more general time-scaling control that allows for speed transitions in arbitrary time. As prior work has focused on po...

Central pattern generators for bipedal locomotion.

Golubitsky, Stewart, Buono and Collins proposed two models for the achitecture of central pattern generators (CPGs): one for bipeds (which we call leg) and one for quadrupeds (which we call quad). In this paper we use symmetry techniques to classify the possible spatiotemporal symmetries of periodic solutions that can exist in leg (there are 10 nontrivial types) and we explore the possibility t...

Towards Muscle Driven Bipedal Locomotion

Multi-contact bipedal robotic locomotion

This paper presents a formal framework for achieving multi-contact bipedal robotic walking, and realizes this methodology experimentally on two robotic platforms: AMBER2 and ATRIAS. Inspired by the key feature encoded in human walking— multi-contact behavior—this approach begins with the analysis of human locomotion and uses it to motivate the construction of a hybrid system model representing ...