A genetic algorithm for multi-robot routing in automated bridge inspection
We attack the problem of generating balanced and efficient routing for automated inspection by using genetic algorithms to solve the equivalent Min-Max k Windy Chinese Postman Problem. Specifically, we use k robots to collectively inspect every member of a steel truss bridge. Experimental results show that the genetic algorithm produces efficient routes that are well-balanced among the robots. Additionally, we demonstrate that with our novel representation, as the number of robots increases, the generated routes exhibit near-linear speedup in the time needed to complete the inspection task - k robots take k1 th the time needed by one robot. Finally, our genetic algorithm produces similar results on a set of benchmark arc routing problem instances from the literature.
Arc routing, Bridge inspection, Genetic algorithms, Robot inspection
Harris, Nicholas, Siming Liu, Sushil J. Louis, and Jim Hung La. "A genetic algorithm for multi-robot routing in automated bridge inspection." In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 369-370. 2019.
GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion