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, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October, 2016

View Publication

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.


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.

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 = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
year = {2016},
month = {October},
} 2017-09-13T10:38:14-04:00