Simultaneous multi-vehicle control and obstacle avoidance using supervised optimal planning

This paper presents a novel approach to control the formation of a group of unmanned ground vehicles in an outdoor environment. Using Lyapunov stability analysis, a closed loop control law for a differential-drive vehicle is derived to maintain its target position in the formation. This control law is combined with an optimal control strategy to avoid obstacles. A simple fuzzy logic supervisor balances the weight each algorithm has on the output control signals by gradually allowing the obstacle avoidance to take over the steering as obstacles become close. Simulations have shown this supervised optimal control strategy to be an effective algorithm that seamlessly allows the group of vehicles to temporarily break formation to avoid obstacles.