POMHDP: Search-based belief space planning using multiple heuristics

Sung Kyun Kim, Oren Salzman, Maxim Likhachev

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Robots operating in the real world encounter substantial uncertainty that cannot be modeled deterministically before the actual execution. This gives rise to the necessity of robust motion planning under uncertainty also known as belief space planning. Belief space planning can be formulated as Partially Observable Markov Decision Processes (POMDPs). However, computing optimal policies for non-trivial POMDPs is computationally intractable. Building upon recent progress from the search community, we propose a novel anytime POMDP solver, Partially Observable Multi-Heuristic Dynamic Programming (POMHDP), that leverages multiple heuristics to efficiently compute high-quality solutions while guaranteeing asymptotic convergence to an optimal policy. Through iterative forward search, POMHDP utilizes domain knowledge to solve POMDPs with specific goals and an infinite horizon. We demonstrate the efficacy of our proposed framework on a real-world, highly-complex, truck unloading application.

Original languageEnglish
Title of host publicationProceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019
EditorsJ. Benton, Nir Lipovetzky, Eva Onaindia, David E. Smith, Siddharth Srivastava
Pages734-744
Number of pages11
ISBN (Electronic)9781577358077
StatePublished - 2019
Externally publishedYes
Event29th International Conference on Automated Planning and Scheduling, ICAPS 2019 - Berkeley, United States
Duration: 11 Jul 201915 Jul 2019

Publication series

NameProceedings International Conference on Automated Planning and Scheduling, ICAPS

Conference

Conference29th International Conference on Automated Planning and Scheduling, ICAPS 2019
Country/TerritoryUnited States
CityBerkeley
Period11/07/1915/07/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management

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