N-dimensional Convex Obstacle Avoidance using Hybrid Feedback Control (Extended version)
Abstract
This paper addresses the autonomous robot navigation problem in a priori unknown n-dimensional environments containing disjoint convex obstacles of arbitrary shapes and sizes, with pairwise distances strictly greater than the robot's diameter. We propose a hybrid feedback control scheme that guarantees safe and global asymptotic convergence of the robot to a predefined target location. The proposed control strategy relies on a switching mechanism allowing the robot to operate either in the move-to-target mode or the obstacle-avoidance mode, based on its proximity to the obstacles and the availability of a clear straight path between the robot and the target. In the obstacle-avoidance mode, the robot is constrained to move within a two-dimensional plane that intersects the obstacle being avoided and the target, preventing it from retracing its path. The effectiveness of the proposed hybrid feedback controller is demonstrated through simulations in two-dimensional and three-dimensional environments.
Cite
@article{arxiv.2403.11279,
title = {N-dimensional Convex Obstacle Avoidance using Hybrid Feedback Control (Extended version)},
author = {Mayur Sawant and Ilia Polushin and Abdelhamid Tayebi},
journal= {arXiv preprint arXiv:2403.11279},
year = {2025}
}
Comments
22 pages, 21 figures