Distributed Knowledge Leader Selection for Multi-Robot Environmental Sampling Under Bandwidth Constraints - Robotics Institute Carnegie Mellon University

Distributed Knowledge Leader Selection for Multi-Robot Environmental Sampling Under Bandwidth Constraints

Wenhao Luo, Shehzaman Salim Khatib, Sasanka Nagavalli, Nilanjan Chakraborty, and Katia Sycara
Conference Paper, Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5751 - 5757, October, 2016

Abstract

In many multi-robot applications such as target search, environmental monitoring and reconnaissance, the multi-robot system operates semi-autonomously, but under the supervision of a remote human who monitors task progress. In these applications, each robot collects a large amount of task-specific data that must be sent to the human periodically to keep the human aware of task progress. It is often the case that the human-robot communication links are extremely bandwidth constrained and/or have significantly higher latency than inter-robot communication links, so it is impossible for all robots to send their task-specific data together. Thus, only a subset of robots, which we call the knowledge leaders, can send their data at a time. In this paper, we study the knowledge leader selection problem, where the goal is to select a subset of robots with a given cardinality that transmits the most informative task-specific data for the human. We prove that the knowledge leader selection is a submodular function maximization problem under explicit conditions and present a novel distributed submodular optimization algorithm that has the same approximation guarantees as the centralized greedy algorithm. The effectiveness of our approach is demonstrated using numerical simulations.

BibTeX

@conference{Luo-2016-5604,
author = {Wenhao Luo and Shehzaman Salim Khatib and Sasanka Nagavalli and Nilanjan Chakraborty and Katia Sycara},
title = {Distributed Knowledge Leader Selection for Multi-Robot Environmental Sampling Under Bandwidth Constraints},
booktitle = {Proceedings of (IROS) IEEE/RSJ International Conference on Intelligent Robots and Systems},
year = {2016},
month = {October},
pages = {5751 - 5757},
}