Abstract
Embedding elastic elements into legged robots through mechanical design enables highly efficient oscillating patterns that resemble natural gaits. However, current trajectory planning techniques miss the opportunity of taking advantage of these natural motions. This work proposes a locomotion planning method that aims to unify traditional trajectory generation with modal oscillations. Our method utilizes task-space linearized modes for generating center of mass trajectories on the sagittal plane. We then use nonlinear optimization to find the gait timings that match these trajectories within the Divergent Component of Motion planning framework. This way, we can robustly translate the modes-aware centroidal motions into joint coordinates. We validate our approach with promising results and insights through experiments on a compliant quadrupedal robot.
Original language | English |
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Title of host publication | Proceedings of the International Conference on Robotics and Automation (ICRA 2022) |
Editors | George J. Pappas, Vijay Kumar |
Publisher | IEEE |
Pages | 6593-6599 |
ISBN (Electronic) | 978-1-7281-9681-7 |
ISBN (Print) | 978-1-7281-9680-0 |
DOIs | |
Publication status | Published - 2022 |
Event | 2022 International Conference on Robotics and Automation (ICRA) - Philadelphia, United States Duration: 23 May 2022 → 27 May 2022 Conference number: 39 |
Conference
Conference | 2022 International Conference on Robotics and Automation (ICRA) |
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Abbreviated title | ICRA 2022 |
Country/Territory | United States |
City | Philadelphia |
Period | 23/05/22 → 27/05/22 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- Legged locomotion
- Trajectory planning
- Robot kinematics
- Trajectory
- Planning
- Timing
- Quadrupedal robots