Hybrid Feedback for Autonomous Navigation in Environments with Arbitrary Convex Obstacles

TL;DR

This paper presents a hybrid feedback control algorithm for autonomous robot navigation in 2D environments with arbitrary convex obstacles, ensuring safe, stable, and goal-directed movement.

Contribution

It introduces a novel hybrid control strategy with a switching mechanism for obstacle avoidance and target navigation, validated through simulations.

Findings

Guarantees global asymptotic stabilization to the target

Ensures forward invariance of obstacle-free space

Effective sensor-based implementation demonstrated

Abstract

We develop an autonomous navigation algorithm for a robot operating in two-dimensional environments cluttered with obstacles having arbitrary convex shapes. The proposed navigation approach relies on a hybrid feedback to guarantee global asymptotic stabilization of the robot towards a predefined target location while ensuring the forward invariance of the obstacle-free workspace. The main idea consists in designing an appropriate switching strategy between the move-to-target mode and the obstacle-avoidance mode based on the proximity of the robot with respect to the nearest obstacle. The proposed hybrid controller generates continuous velocity input trajectories when the robot is initialized away from the boundaries of the unsafe regions. Finally, we provide an algorithmic procedure for the sensor-based implementation of the proposed hybrid controller and validate its effectiveness through some simulation results.