<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In ZMP trajectory generation using simple models, often a considerable amount of trials and errors are involved to obtain locally stable gaits by manually tuning the gait parameters. In this paper a 15 degrees of Freedom dynamic model of a compliant humanoid robot is used, combined with reinforcement learning to perform global search in the parameter space to produce stable gaits. It is shown that for a given speed, multiple sets of parameters, namely step sizes and lateral sways, are obtained by the learning algorithm which can lead to stable walking. The resulting set of gaits can be further studied in terms of parameter sensitivity and also to include additional optimization criteria to narrow down the chosen walking trajectories for the humanoid robot.</p></abstract>

In ZMP trajectory generation using simple models, often a considerable amount of trials and errors are involved to obtain locally stable gaits by manually tuning the gait parameters. In this paper a 15 degrees of Freedom dynamic model of a compliant humanoid robot is used, combined with reinforcement learning to perform global search in the parameter space to produce stable gaits. It is shown that for a given speed, multiple sets of parameters, namely step sizes and lateral sways, are obtained by the learning algorithm which can lead to stable walking. The resulting set of gaits can be further studied in terms of parameter sensitivity and also to include additional optimization criteria to narrow down the chosen walking trajectories for the humanoid robot.

On Global Optimization of Walking Gaits for the Compliant Humanoid Robot, COMAN Using Reinforcement Learning

Department of Advanced Robotics, Istituto Italiano di Tecnologia, via Morego 30, 16163 Genova

Cybernetics and Information Technologies

In ZMP trajectory generation using simple models, often a considerable amount of trials and errors are involved to obtain locally stable gaits by manually...

On Global Optimization of Walking Gaits for the Compliant Humanoid Robot, COMAN Using Reinforcement Learning

Online veröffentlicht: 22. März 2013

Seitenbereich: 39 - 52

DOI: https://doi.org/10.2478/cait-2012-0020

Schlüsselwörter
Humanoid robot walking, compliance, reinforcement learning

This content is open access.

On Global Optimization of Walking Gaits for the Compliant Humanoid Robot, COMAN Using Reinforcement Learning

Online veröffentlicht: 22. März 2013

Seitenbereich: 39 - 52

DOI: https://doi.org/10.2478/cait-2012-0020

SchlüsselwörterHumanoid robot walking, compliance, reinforcement learning

This content is open access.

Schlüsselwörter
Humanoid robot walking, compliance, reinforcement learning