Agboh, WC orcid.org/0000-0002-0242-0215 and Dogar, MR orcid.org/0000-0002-6896-5461 (2020) Pushing Fast and Slow: Task-Adaptive Planning for Non-prehensile Manipulation Under Uncertainty. In: Algorithmic Foundations of Robotics XIII: Proceedings of the 13th Workshop on the Algorithmic Foundations of Robotics, Springer Proceedings in Advanced Robotics (SPAR). 13th International Workshop on the Algorithmic Foundations of Robotics (WAFR 2018), 09-11 Dec 2018, Mérida, Yucatán, México. Springer ISBN 978-3-030-44051-0
Abstract
We propose a planning and control approach to physics-based manipulation. The key feature of the algorithm is that it can adapt to the accuracy requirements of a task, by slowing down and generating "careful" motion when the task requires high accuracy, and by speeding up and moving fast when the task tolerates inaccuracy.We formulate the problem as an MDP with action-dependent stochasticity and propose an approximate online solution to it.We use a trajectory optimizer with a deterministic model to suggest promising actions to the MDP, to reduce computation time spent on evaluating different actions. We conducted experiments in simulation and on a real robotic system. Our results show that with a task-adaptive planning and control approach, a robot can choose fast or slow actions depending on the task accuracy and uncertainty level. The robot makes these decisions online and is able to maintain high success rates while completing manipulation tasks as fast as possible.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2020. This is an author produced version of a paper published in Algorithmic Foundations of Robotics XIII: Proceedings of the 13th Workshop on the Algorithmic Foundations of Robotics, Springer Proceedings in Advanced Robotics (SPAR). Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | motion and path planning; robotic manipulation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/P019560/1 EU - European Union 746143 EPSRC (Engineering and Physical Sciences Research Council) EP/R031193/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 22 Jan 2019 11:22 |
Last Modified: | 30 Jan 2022 20:33 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-030-44051-0_10 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:141371 |