Dynamic Feedback Motion Planning for Car-Like Robots Using Funnel-Graph Algorithm

Abstract

This study presents a funnel-based motion planning algorithm for a car-like robot, utilizing a dynamic model to capture the robot's motion. The funnel-based planner addresses the obstacle avoidance problem and dynamically updates the path to guide the robot to its goal. The proposed algorithm's performance is evaluated in a dynamic environment, and with a dynamic goal where re-planning capabilities are demonstrated. The results indicate that funnel planner provides robust navigation even in uncertain conditions.