Corpus ID: 201714753

Belief-Space Planning using Learned Models with Application to Underactuated Hands

@inproceedings{Kimmel2020BeliefSpacePU,
  title={Belief-Space Planning using Learned Models with Application to Underactuated Hands},
  author={Andrew Kimmel and Avishai Sintov and Juntao Tan and Bowen Wen and Abdeslam Boularias and Kostas E. Bekris},
  year={2020}
}
Acquiring a precise model is a challenging task for many important robotic tasks and systems including in-hand manipulation using underactuated, adaptive hands. Learning stochastic, data-driven models is a promising alternative as they provide not only a way to propagate forward the system dynamics, but also express the uncertainty present in the collected data. Therefore, such models enable planning in the space of state distributions, i.e., in the belief space. This paper proposes a planning… Expand

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