Dynamic Path Planning Algorithm for Autonomous Vehicles in Cluttered Environments

In this paper, a method of dynamic path planning algorithm for autonomous vehicles in cluttered environments is presented. The proposed method is based on the D* Lite algorithm with a smoothing method and local optimisation to enhance its performance in cluttered environments. The Lowess smoothing method has useful properties for the path planning problem especially in complex environments which involve lots of corners or direction changes required to avoid dynamic obstacles. Cubic Hermite spline interpolation is used to describe curvature continuous trajectories for autonomous vehicles. Knowing the start and goal position, a continuous smooth trajectory can be decided. Results of proposed method are shown in simulations and experiments. Trajectories are demonstrated in various environments with and without additional obstacles. Quantitative results are shown and analysed to validate the proposed method.