Effective navigation in narrow areas: A planning method for autonomous cars

Development of driverless road vehicles is one of the most active research areas of robotics today. Path planning among obstacles is one of the challenging problems to be solved in order to achieve autonomous navigation. In this paper we present a geometric path planning approach for car-like robots, intended for generating good quality paths even in cluttered environments containing narrow areas. The presented planner is designed to cope with situations which need nontrivial maneuvering between obstacles. The resulting paths are similar to those a human driver would find and have continuous curvature profile, which makes them appropriate for application on real cars. A comparative analysis of our method with possible alternatives in the literature is presented to illustrate its effectiveness regarding path quality and computation time.