Reactive Kinematic Navigation among Moving and Deforming Obstacles with Global Proofs

TL;DR

This paper introduces a biologically inspired control law for guiding a Dubins-like vehicle through maze-like environments with moving and deforming obstacles, ensuring convergence and verified by simulations and real robot experiments.

Contribution

It presents a novel reflex-based control method with rigorous analysis for navigation in complex, dynamic environments, including proofs of convergence.

Findings

Control law guarantees convergence to target

Validated through computer simulations

Confirmed by experiments with real robots

Abstract

We present a method for guidance of a Dubins-like vehicle with saturated control towards a target in a steady simply connected maze-like environment. The vehicle always has access to to the target relative bearing angle (even if the target is behind the obstacle or is far from the vehicle) and the distance to the nearest point of the maze if it is within the given sensor range. The proposed control law is composed by biologically inspired reflex-level rules. Mathematically rigorous analysis of this law is provided; its convergence and performance are confirmed by computer simulations and experiments with real robots.