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Counterexample guided inductive optimization applied to mobile robots path planning

Abstract:

We describe and evaluate a novel optimization-based off-line path planning algorithm for mobile robots based on the Counterexample-Guided Inductive Optimization (CEGIO) technique. CEGIO iteratively employs counterexamples generated from Boolean Satisfiability (SAT) and Satisfiability Modulo Theories (SMT) solvers, in order to guide the optimization process and to ensure global optimization. This paper marks the first application of CEGIO for planning mobile robot path. In particular, CEGIO ha...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/SBR-LARS-R.2017.8215336

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
Publisher:
IEEE
Host title:
2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR)
Journal:
14th Latin American Robotics Symposium (LARS 2017) More from this journal
Publication date:
2017-12-18
Acceptance date:
2017-07-26
DOI:
ISBN:
9781538609569
Keywords:
Pubs id:
pubs:713706
UUID:
uuid:24a86a92-f31f-4145-a42e-e09d090990a4
Local pid:
pubs:713706
Source identifiers:
713706
Deposit date:
2017-08-14

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