| Document Date: 2012-02-11 15:07:06
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Company Artificial Intelligence Laboratory / / / Facility Massachusetts Institute of Technology / / IndustryTerm Online planning algorithms / belief space planning algorithm / point-based algorithms / re-planning algorithm / direct transcription solution / overall algorithm / e-h / / Organization National Science Foundation / MIT / Computer Science and Engineering Department / SUNY / Massachusetts Institute of Technology / / Person Leslie Kaelbling / Tomas Lozano-Perez / Robert Platt / / Position model control problems / high-sample planner / low-sample planner / planner / LQG-MP / IRT RAN planner / / Product Altec XT1 Speakers / / ProvinceOrState Massachusetts / / PublishedMedium The Journal of Machine Learning Research / / Technology laser / point-based algorithms / belief space planning algorithm / Online planning algorithms / overall algorithm / re-planning algorithm / planning algorithm / Point-based POMDP algorithms / Machine Learning / LGORITHM The algorithm / hypothesis-based algorithm / pdf / /
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Non-Gaussian Belief Space Planning: Correctness and Complexity Robert Platt, Leslie Kaelbling, Tomas Lozano-Perez, Russ Tedrake Abstract— We consider the partially observable control problem where it is potentially nec