A Switching Planner for Combined Task and Observation Planning

Authors

  • Moritz Göbelbecker Albert-Ludwigs-Universität Freiburg
  • Charles Gretton University of Birmingham
  • Richard Dearden University of Birmingham

DOI:

https://doi.org/10.1609/aaai.v25i1.8011

Abstract

From an automated planning perspective the problem of practical mobile robot control in realistic environments poses many important and contrary challenges. On the one hand, the planning process must be lightweight, robust, and timely. Over the lifetime of the robot it must always respond quickly with new plans that accommodate exogenous events, changing objectives, and the underlying unpredictability of the environment. On the other hand, in order to promote efficient behaviours the planning process must perform computationally expensive reasoning about contingencies and possible revisions of subjective beliefs according to quantitatively modelled uncertainty in acting and sensing. Towards addressing these challenges, we develop a continual planning approach that switches between using a fast satisficing "classical" planner, to decide on the overall strategy, and decision-theoretic planning to solve small abstract subproblems where deeper consideration of the sensing model is both practical, and can significantly impact overall performance. We evaluate our approach in large problems from a realistic robot exploration domain.

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Published

2011-08-04

How to Cite

Göbelbecker, M., Gretton, C., & Dearden, R. (2011). A Switching Planner for Combined Task and Observation Planning. Proceedings of the AAAI Conference on Artificial Intelligence, 25(1), 964-970. https://doi.org/10.1609/aaai.v25i1.8011

Issue

Section

Reasoning about Plans, Processes and Actions