Conference item
CPG-ACTOR: reinforcement learning for central pattern generators
- Abstract:
-
Central Pattern Generators (CPGs) have several properties desirable for locomotion: they generate smooth trajectories, are robust to perturbations and are simple to implement. However, they are notoriously difficult to tune and commonly operate in an open-loop manner. This paper proposes a new methodology that allows tuning CPG controllers through gradient-based optimisation in a Reinforcement Learning (RL) setting. In particular, we show how CPGs can directly be integrated as the Actor in an...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
-
(Accepted manuscript, pdf, 1.0MB)
-
- Publisher copy:
- 10.1007/978-3-030-89177-0_3
Authors
Bibliographic Details
- Publisher:
- Springer Publisher's website
- Host title:
- Towards Autonomous Robotic Systems
- Series:
- Lecture Notes in Computer Science
- Series number:
- 13054
- Pages:
- 25-35
- Place of publication:
- Cham, Switzerland
- Publication date:
- 2021-10-31
- Acceptance date:
- 2021-07-01
- Event title:
- Towards Autonomous Robotic Systems Conference (TAROS 2021)
- Event location:
- Lincoln, UK
- Event website:
- https://lcas.lincoln.ac.uk/wp/taros-2021/
- Event start date:
- 2021-09-08
- Event end date:
- 2021-09-10
- DOI:
- EISSN:
-
1611-3349
- ISSN:
-
0302-9743
- EISBN:
- 9783030891770
- ISBN:
- 9783030891763
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1212770
- Local pid:
- pubs:1212770
- Deposit date:
- 2023-01-23
Terms of use
- Copyright holder:
- Springer Nature Switzerland AG
- Copyright date:
- 2021
- Rights statement:
- © 2021 Springer Nature Switzerland AG.
- Notes:
- This is the accepted manuscript version of the paper. The final version is available online from Springer at: https://doi.org/10.1007/978-3-030-89177-0_3
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