Intelligent control and evolutionary strategies applied to multirobotic systems

This paper describes the modeling, implementation, and evaluation of RoBombeiros multirobotic system. The robotic task in this paper is performed over a natural disaster, simulated as a forest fire. The simulator supports several features to allow realistic simulation, like irregular terrains, natural processes (e.g. fire, wind) and physical constraint in the creation and application of mobile robots. The proposed system relies on two steps: (i) group formation planning and (ii) intelligent techniques to perform robots navigation for fire fighting. For planning, we used genetic algorithms to evolve positioning strategies for firefighting robots performance. For robots operation, physically simulated fire-fighting robots were built, and the sensory information of each robot (e.g. GPS, compass, sonar) was used in the input of an artificial neural network (ANN). The ANN controls the vehicle (robot) actuators and allows navigation with obstacle avoidance. Simulation results show that the ANN satisfactorily controls the mobile robots; the genetic algorithm adequately configures the fire fighting strategy and the proposed multi-robotic system can have an essential hole in the planning and execution of fire fighting in real forests.