Path planning and following using genetic algorithms to solve the multi-travel salesman problem in dynamic scenarios

This paper presents an implementation of a technique to solve the Multi-Travel Salesman Problem (MTSP) when applied to mobile robots in dynamic scenarios. Given that the MTSP is an NP-Complete problem, we used genetic algorithms to solve it efficiently. Once we obtained a theoretical solution for the MTSP, we applied it in simulated and experimental scenarios. In addition, we implemented path planning algorithms to generate the path for each of the robots, and evasion algorithms to manage dynamic scenarios. With those main challenges clear, we tested these implementations in simulation and laboratory environments in order to measure the quality of the proposed solution.