Anchor-Oriented Localized Voronoi Partitioning for GPS-denied Multi-Robot Coverage

TL;DR

This paper introduces an anchor-oriented localized Voronoi partitioning method for multi-robot coverage in GPS-denied environments, enabling effective coordination without global localization.

Contribution

It presents a novel anchor-oriented coverage approach with localized Voronoi partitions and a consensus-based coordination algorithm for GPS-denied multi-robot exploration.

Findings

Performs comparably to GPS-based methods in simulations and real-world tests.

Enables multi-robot coverage without reliance on global positioning.

Demonstrates effectiveness in GPS-denied, extreme environments.

Abstract

Multi-robot coverage is crucial in numerous applications, including environmental monitoring, search and rescue operations, and precision agriculture. In modern applications, a multi-robot team must collaboratively explore unknown spatial fields in GPS-denied and extreme environments where global localization is unavailable. Coverage algorithms typically assume that the robot positions and the coverage environment are defined in a global reference frame. However, coordinating robot motion and ensuring coverage of the shared convex workspace without global localization is challenging. This paper proposes a novel anchor-oriented coverage (AOC) approach to generate dynamic localized Voronoi partitions based around a common anchor position. We further propose a consensus-based coordination algorithm that achieves agreement on the coverage workspace around the anchor in the robots' relative frames of reference. Through extensive simulations and real-world experiments, we demonstrate that the proposed anchor-oriented approach using localized Voronoi partitioning performs as well as the state-of-the-art coverage controller using GPS.