Evaluation of a Fault-tolerant Model for Tactic Operations of Mobile Robotic Groups Using Genetic Algorithms

This paper addresses the evaluation of a fault-tolerant model for tactic operations of mobile robotic groups. The coordinated action of the group is planned with Genetic Algorithms (GA) and aims to act on an environmental disaster scenario, simulated as a forest fire. The robotic squad should surround the fire and avoid fire's propagation. Initially, we evaluate several parameters in the GA, seeking to obtain the set of parameters that would accomplish the more efficient evolution. Then, we simulate failures in robots operations in order to evaluate strategies of reorganization. The simulation's results 1 showed that with an adequate set of parameters it is possible to get satisfactory strategic positions to coordinate and to reorganize the robotic group in case of robot failures.