Planning Smooth and Safe Control Laws for a Unicycle Robot Among Obstacles
For roboticists, this provides a computationally efficient, provably safe control method for unicycle robots in obstacle environments.
This paper introduces a framework for safe unicycle robot navigation using a smooth vector field and an analytic feedback controller that guarantees forward invariance of the safe set without online optimization. Simulations show twice faster arrival time and over 50% lower angular control effort compared to baselines.
This paper presents a framework for safe navigation of a unicycle point robot to a goal position in an environment populated with obstacles from almost any admissible state, considering input limits. We introduce a novel QP formulation to create a Cinfinity-smooth vector field with reduced total bending and total turning. Then we design an analytic, non-linear feedback controller that inherently satisfies the conditions of Nagumo's theorem, ensuring forward invariance of the safe set without requiring any online optimization. We have demonstrated that our controller, even under hard input limits, safely converges to the goal position. Simulations confirm the effectiveness of the proposed framework, resulting in a twice faster arrival time with over 50\% lower angular control effort compared to the baseline.