IROS 2024poster0 citations

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

Aiman Munir, Ehsan Latif, Ramviyas Parasuraman

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.

BibTeX
@inproceedings{iros2024_anchororientedlo,
  title = {Anchor-Oriented Localized Voronoi Partitioning for GPS-denied Multi-Robot Coverage},
  author = {Aiman Munir and Ehsan Latif and Ramviyas Parasuraman},
  booktitle = {IROS 2024},
  year = {2024}
}
Anchor-Oriented Localized Voronoi Partitioning for GPS-denied Multi-Robot Coverage · IROS 2024