Journal
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
Volume 32, Issue 9-10, Pages 1194-1227Publisher
SAGE PUBLICATIONS LTD
DOI: 10.1177/0278364913484072
Keywords
manipulation planning; planning under uncertainty; symbolic task planning; belief space; mobile manipulation
Categories
Funding
- NSF [1117325]
- ONR MURI [N00014-09-1-1051]
- AFOSR [FA2386-10-1-4135]
- Singapore Ministry of Education
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1117325] Funding Source: National Science Foundation
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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 logical expressions that describe sets of belief states, which are goals and subgoals in the planning process. We show that a relatively small set of symbolic operators can give rise to task-oriented perception in support of the manipulation goals. An implementation of this method is demonstrated in simulation and on a real PR2 robot, showing robust, flexible solution of mobile manipulation problems with multiple objects and substantial uncertainty.
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