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Time-Optimal Navigation in Uncertain Environments with High-Level Specifications

Rosolia, Ugo and Ahmadi, Mohamadreza and Murray, Richard M. and Ames, Aaron D. (2021) Time-Optimal Navigation in Uncertain Environments with High-Level Specifications. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20210511-085123358

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Abstract

Mixed observable Markov decision processes (MOMDPs) are a modeling framework for autonomous systems described by both fully and partially observable states. In this work, we study the problem of synthesizing a control policy for MOMDPs that minimizes the expected time to complete the control task while satisfying syntactically co-safe Linear Temporal Logic (scLTL) specifications. First, we present an exact dynamic programming update to compute the value function. Afterwards, we propose a point-based approximation, which allows us to compute a lower bound of the closed-loop probability of satisfying the specifications. The effectiveness of the proposed approach and comparisons with standard strategies are shown on high-fidelity navigation tasks with partially observable static obstacles.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
http://arxiv.org/abs/2103.01476arXivDiscussion Paper
ORCID:
AuthorORCID
Rosolia, Ugo0000-0002-1682-0551
Ahmadi, Mohamadreza0000-0003-1447-3012
Murray, Richard M.0000-0002-5785-7481
Ames, Aaron D.0000-0003-0848-3177
Record Number:CaltechAUTHORS:20210511-085123358
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210511-085123358
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109069
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:11 May 2021 17:10
Last Modified:11 May 2021 17:10

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