Anchor-Oriented Localized Voronoi Partitioning for GPS-denied Multi-Robot Coverage
Munir, Aiman, Latif, Ehsan, Parasuraman, Ramviyas
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Jul-8-2024
- Country:
- Europe (0.04)
- North America > United States
- Georgia > Clarke County > Athens (0.14)
- Genre:
- Research Report (0.50)
- Industry:
- Food & Agriculture > Agriculture (0.54)
- Technology: