English

A Study on Multirobot Quantile Estimation in Natural Environments

Robotics 2023-07-10 v2 Multiagent Systems

Abstract

Quantiles of a natural phenomena can provide scientists with an important understanding of different spreads of concentrations. When there are several available robots, it may be advantageous to pool resources in a collaborative way to improve performance. A multirobot team can be difficult to practically bring together and coordinate. To this end, we present a study across several axes of the impact of using multiple robots to estimate quantiles of a distribution of interest using an informative path planning formulation. We measure quantile estimation accuracy with increasing team size to understand what benefits result from a multirobot approach in a drone exploration task of analyzing the algae concentration in lakes. We additionally perform an analysis on several parameters, including the spread of robot initial positions, the planning budget, and inter-robot communication, and find that while using more robots generally results in lower estimation error, this benefit is achieved under certain conditions. We present our findings in the context of real field robotic applications and discuss the implications of the results and interesting directions for future work.

Keywords

Cite

@article{arxiv.2303.03539,
  title  = {A Study on Multirobot Quantile Estimation in Natural Environments},
  author = {Isabel M. Rayas Fernández and Christopher E. Denniston and Gaurav S. Sukhatme},
  journal= {arXiv preprint arXiv:2303.03539},
  year   = {2023}
}

Comments

7 pages, 2 tables, 7 figures

R2 v1 2026-06-28T09:04:33.276Z