Path Planning Under MIMO Network Constraints for Throughput Enhancement in Multi-robot Data Aggregation Tasks
Alexandra Pogue, Samer Hanna, Andy Nichols, Xin Chen, Danijela Cabric, Ankur Mehta
Abstract
Under line-of-sight (LOS) network conditions, multi-input multi-output (MIMO) wireless communications can increase the channel capacity between a team of robots and a multi-antenna array at a stationary base station. This increased capacity can result in greater data throughput, shortening the time necessary to complete channel-limited data aggregation tasks. To take advantage of this higher capacity channel, the robots in the team must be positioned to maximize complex channel orthogonality between each robot and receiver antenna. Using geometrically motivated assumptions, we derive transmitter spacing rules that can be easily be added on to existing path plans to improve backhaul throughput for data offloading from the robot team, with minimal impact on other system objectives. We demonstrate the effectiveness of the approach- both in ideal as well as realistic channels outside the domain of our simplifying assumptions-with numerical examples of robot-coordinated path plans in two example environments, achieving up to 42% improvement in task completion times.
BibTeX
@inproceedings{iros2020_pathplanningunde,
title = {Path Planning Under MIMO Network Constraints for Throughput Enhancement in Multi-robot Data Aggregation Tasks},
author = {Alexandra Pogue and Samer Hanna and Andy Nichols and Xin Chen and Danijela Cabric and Ankur Mehta},
booktitle = {IROS 2020},
year = {2020}
}