Distributed surveillance by a swarm of UAVs operating under positional uncertainty

TL;DR

This paper presents a distributed control framework for UAV swarms with positional uncertainty, enabling optimal visual coverage of a region through a Voronoi-free tessellation and gradient-based approach, validated by simulations.

Contribution

It introduces a novel distributed control method for UAV swarms with sensor uncertainty, achieving optimal coverage without Voronoi partitioning.

Findings

Effective coverage achieved in simulations

Distributed self-organization without Voronoi tessellation

Monotonic convergence to optimal coverage

Abstract

This article proposes a collaborative control framework for an autonomous aerial swarm tasked with the surveillance of a convex region of interest. Each Mobile Aerial Agent (MAA) is equipped with a Pan-Tilt-Zoom (PTZ) camera of conical FOV and suffers from sensor-induced positional uncertainty. By utilizing a Voronoi-free tessellation strategy and a gradient scheme, the heterogeneous swarm self-organizes in a distributed manner to monotonically achieve optimal collective visual coverage of the region of interest, both in terms of quality and total area. Simulation studies are offered to investigate the effectiveness of the suggested scheme.