Planning trajectories in dynamic environments using a gradient method

In this article we propose an extension for a path planning method based on the LPN-algorithm to have better performance in a very dynamic environment. The path planning method builds a navigation function that drives the robot toward the goal avoiding the obstacles. The basic method is very fast and efficient for a robot with few degrees of freedom. The proposed extension integrates the obstacle dynamics in the planning method to have better performances in very dynamic environments. Experiments have shown the effectiveness of the proposed extension in a very dynamic environment, given by RoboCup soccer matches.