Conference item
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 has been successfully applied to obtain optimal two-dimensional paths for autonomous mobile robots using off-the-shelf SAT and SMT solvers.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 220.6KB, Terms of use)
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- Publisher copy:
- 10.1109/SBR-LARS-R.2017.8215336
Authors
- 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:
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pubs:713706
- UUID:
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uuid:24a86a92-f31f-4145-a42e-e09d090990a4
- Local pid:
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pubs:713706
- Source identifiers:
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713706
- Deposit date:
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2017-08-14
- ARK identifier:
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2017
- Notes:
- Copyright © 2017 IEEE. This is the accepted manuscript version of the article. The final version is available online from IEEE at: https://doi.org/10.1109/SBR-LARS-R.2017.8215336
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