Preview optimization for learning locomotion policies on rough terrain

Preview optimization for learning locomotion policies on rough terrain

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...

Bibliografski detalji
Glavni autori:	Mastalli, C, Havoutis, I, Radulescu, A, Focchi, M, Caldwell, D, Semini, C
Format:	Conference item
Izdano:	2016

Slični predmeti

Trajectory and foothold optimization using low-dimensional models for rough terrain locomotion
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High-slope terrain locomotion for torque-controlled quadruped robots
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od: Dai, Hongkai, Ph. D. Massachusetts Institute of Technology
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od: Andras Karsai, i dr.
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od: Brandao, M, i dr.
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Preview
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Preview
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Previews
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