Integrated task and motion planning in belief space
We describe an integrated strategy for planning, perception, state estimation and action in complex mobile manipulation domains based on planning in the belief space of probability distributions over states using hierarchical goal regression (pre-image back-chaining). We develop a vocabulary of logi...
Main Authors: | Kaelbling, Leslie P., Lozano-Perez, Tomas |
---|---|
Other Authors: | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
Format: | Article |
Language: | en_US |
Published: |
Sage Publications
2014
|
Online Access: | http://hdl.handle.net/1721.1/87038 https://orcid.org/0000-0002-8657-2450 https://orcid.org/0000-0001-6054-7145 |
Similar Items
-
Integrated robot task and motion planning in belief space
by: Kaelbling, Leslie Pack, et al.
Published: (2012) -
Integrated Robot Task and Motion Planning in the Now
by: Kaelbling, Leslie Pack, et al.
Published: (2012) -
Learning to guide task and motion planning using score-space representation
by: Kim, Beomjoon, et al.
Published: (2021) -
Hierarchical Task and Motion Planning in the Now
by: Kaelbling, Leslie Pack, et al.
Published: (2010) -
Learning to guide task and motion planning using score-space representation
by: Kim, Beomjoon, et al.
Published: (2021)