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Preview optimization for learning locomotion policies on rough terrain

Abstract:

Legged robots promise a clear advantage in unstructured and challenging terrain, scenarios such as disaster relief, search and rescue, forestry and construction site. Dynamic locomotion on rough terrain has to guarantee stability and maximizing the cross-ability of a local set of candidate footholds. Trajectory optimization improves such performance metric while satisfying locomotion stability. Terrain conditions increase significantly the dimensionality of the optimization problem. Moreover,...

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Publication status:
Not published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0002-4371-4623
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Journal:
Workshop on Dynamic Locomotion and Manipulation with Complex Robotic Systems in the Real World (DLMC 2016) Journal website
Host title:
Workshop on Dynamic Locomotion and Manipulation with Complex Robotic Systems in the Real World (DLMC 2016)
Publication date:
2016-07-14
Acceptance date:
2016-06-03
Source identifiers:
822553
Pubs id:
pubs:822553
UUID:
uuid:35dcc960-2ae9-438c-bdfb-1a1ea85c04c2
Local pid:
pubs:822553
Deposit date:
2018-02-02

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