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Minimum-violation LTL planning with conflicting specifications

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Author(s)
Tumova, Jana
•
Reyes Castro, Luis Ignacio
•
Karaman, Sertac
•
Frazzoli, Emilio
•
Rus, Daniela L.
Date Issued
June 2013
Journal
Proceedings of the 2013 American Control Conference (ACC)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Tumova, Jana et al. "Minimum-violation LTL planning with conflicting specifications." IEEE American Control Conference, 2013.
Version
Original manuscript
Abstract
We consider the problem of automatic generation of control strategies for robotic vehicles given a set of high-level mission specifications, such as “Vehicle x must eventually visit a target region and then return to a base,” “Regions A and B must be periodically surveyed,” or “None of the vehicles can enter an unsafe region.” We focus on instances when all of the given specifications cannot be reached simultaneously due to their incompatibility and/or environmental constraints. We aim to find the least-violating control strategy while considering different priorities of satisfying different parts of the mission. Formally, we consider the missions given in the form of linear temporal logic formulas, each of which is assigned a reward that is earned when the formula is satisfied. Leveraging ideas from the automata-based model checking, we propose an algorithm for finding an optimal control strategy that maximizes the sum of rewards earned if this control strategy is applied. We demonstrate the proposed algorithm on an illustrative case study.
Description
Original manuscript March 15, 2013
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
http://creativecommons.org/licenses/by-nc-sa/3.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/81823
DOI of Published Version
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6579837
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