Online dynamic trajectory optimization and control for a quadruped robot

Cebe, Oguzhan, Tiseo, Carlo, Xin, Guiyang, Lin, Hsiu-chin, Smith, Joshua and Mistry, Michael (2021) Online dynamic trajectory optimization and control for a quadruped robot. 2021 IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 30 May 2021 - 5 Jun 2021. Published in: 2021 IEEE International Conference on Robotics and Automation (ICRA). 12773-12779. IEEE ISSN 1050-4729 ISBN 9781728190785

[img] PDF (© 2021 IEEE) - Accepted Version
Download (7MB)

Abstract

Legged robot locomotion requires the planning of stable reference trajectories, especially while traversing uneven terrain. The proposed trajectory optimization framework is capable of generating dynamically stable base and footstep trajectories for multiple steps. The locomotion task can be defined with contact locations, base motion or both, making the algorithm suitable for multiple scenarios (e.g., presence of moving obstacles). The planner uses a simplified momentum based task space model for the robot dynamics, allowing computation times that are fast enough for online replanning. This fast planning capability also enables the quadruped to accommodate for drift and environmental changes. The algorithm is tested on simulation and a real robot across multiple scenarios, which includes uneven terrain, stairs and moving obstacles. The results show that the planner is capable of generating stable trajectories in the real robot even when a box of 15 cm height is placed in front of its path at the last moment.

Item Type: Conference Proceedings
Additional Information: © 2021 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
Schools and Departments: School of Engineering and Informatics > Engineering and Design
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 20 Dec 2021 09:51
Last Modified: 04 Mar 2022 17:05
URI: http://sro.sussex.ac.uk/id/eprint/103432

View download statistics for this item

📧 Request an update