Switched Vector Field-based Guidance for General Reference Path Following in Planar Environment

TL;DR

This paper introduces a switched vector field guidance method for autonomous vehicles that adapts to real-time errors and angles, ensuring faster convergence and feasible turn rates, validated through theoretical analysis and simulations.

Contribution

It proposes a novel switched vector field guidance approach that improves convergence speed and adherence to vehicle constraints over traditional methods.

Findings

Faster convergence to the reference path.

Guidance commands stay within realistic curvature limits.

Simulation results confirm improved performance.

Abstract

Reference path following is a key component in the functioning of almost all engineered autonomous agents. Among several path following guidance methods in existing literature, vector-field-based guidance approach has got wide attention because of its simplicity and guarantee of stability under a broad class of scenarios. However, the usage of same cross-track-error-dependent structure of desired vector field in most of the existing literature irrespective of instantaneous cross-track error and course angle of unmanned vehicle makes it quite restrictive in attaining faster convergence and also leads to infeasibly high turn rate command for many scenarios. To this end, this paper presents a novel switched vector field-based guidance for following a general reference path, in which the structure of the desired vector field depends on instantaneous cross-track-error and vehicle's course angle. While the developed method ensures faster convergence, it also ensures that the guidance command always stays within a realistic threshold satisfying its curvature constraint, thus making it more real-life implementable for autonomous vehicles with kino-dynamic constraints. Theoretical analysis for convergence of the developed guidance scheme is presented. Possibilities of undesirable chattering at phase transitions are also eliminated. Numerical simulation studies are presented to validate the satisfactory performance of the developed algorithm.