A reformulation of collision avoidance algorithm based on artificial potential fields for fixed-wing UAVs in a dynamic environment

TL;DR

This paper introduces an improved artificial potential field-based collision avoidance algorithm tailored for fixed-wing UAVs operating in dynamic, cluttered environments, emphasizing safety and feasibility.

Contribution

It proposes a novel reformulation of repulsive forces in artificial potential fields specifically for fixed-wing UAVs in dynamic settings.

Findings

Simulation results demonstrate improved collision avoidance performance.

The algorithm effectively navigates in cluttered, dynamic environments.

Future research directions are discussed for further enhancement.

Abstract

As mini UAVs become increasingly useful in the civilian work domain, the need for a method for them to operate safely in a cluttered environment is growing, especially for fixed-wing UAVs as they are incapable of following the stop-decide-execute methodology. This paper presents preliminary research to design a reactive collision avoidance algorithm based on the improved definition of the repulsive forces used in the Artificial potential field algorithms to allow feasible and safe navigation of fixed-wing UAVs in cluttered, dynamic environments. We present simulation results of the improved definition in multiple scenarios, and we have also discussed possible future studies to improve upon these results.