You, Y, Zhou, C orcid.org/0000-0002-6677-0855, Li, Z et al. (1 more author) (2017) A study of nonlinear forward models for dynamic walking. In: 2017 IEEE International Conference on Robotics and Automation (ICRA). 2017 IEEE ICRA, 29 May - 03 Jun 2017, Singapore. IEEE , pp. 3491-3496. ISBN 978-1-5090-4633-1
Abstract
This paper offers a novel insight of using nonlinear models for the control to produce more robust and natural walking gaits for humanoid robots. The sagittal and lateral gait control needs to be treated differently, hence, we proposed two types of suitable nonlinear models, which allow forward simulations to look ahead, and thus, predict accurately the future trajectory/state at the end of the current step. Subsequently, by performing multiple forward simulations in a similar manner for the next step and using the gradient descent method, an appropriate foot placement can be found to achieve precise walking speed. By doing this two-step lookahead, all trajectories of the support and the swing leg can be generated. Our proposed controller can plan trajectories at the beginning of each step or actively re-plan according to task state errors. It is validated effectively in simulations performed in both ADAMS and Open Dynamic Engine. The robot can successfully traverse up/down a stair and recover from pushes with more natural looking gaits compared to the conventional bent-knee style. The reasonable computational time also indicates the feasibility of real-time implementation on real robots.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | Legged locomotion; Foot; Computational modeling; Mathematical model; Predictive models; Dynamics |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 04 Apr 2019 11:51 |
Last Modified: | 04 Apr 2019 11:51 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ICRA.2017.7989399 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144478 |