Smooth reactive collision avoidance in difficult environments

This paper addresses a new obstacle avoidance method for mobile robots moving in dense and complex environments. Our approach, named Smooth Closest Gap (SCG) Navigation, builds on the concept of Closest Gap (CG) as a strategy to detect free openings surrounding the robot and select the most promising one to drive through. Obstacle avoidance is performed based on the configuration of obstacles between the current robot location and the selected gap, where all obstacle points are considered to compute the avoidance maneuver and simultaneously drive the robot towards the gap. Moreover, the free area available to maneuver along the desired heading is taken into account. In turn, unnecessary deflections towards free spaces are avoided, the smoothness of the robot's trajectory is improved, and a greater reliability is achieved. The power of the proposed method is demonstrated by experimental results.