Counterexample Guided Inductive Optimization Applied to Mobile Robots Path Planning (Extended Version)
Robotics
2017-08-15 v1 Artificial Intelligence
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.
Cite
@article{arxiv.1708.04028,
title = {Counterexample Guided Inductive Optimization Applied to Mobile Robots Path Planning (Extended Version)},
author = {Rodrigo F. Araújo and Alexandre Ribeiro and Iury V. Bessa and Lucas C. Cordeiro and João E. C. Filho},
journal= {arXiv preprint arXiv:1708.04028},
year = {2017}
}
Comments
7 pages, 14rd Latin American Robotics Symposium (LARS'2017)