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.