Multi-modal User Interface for Multi-robot Control in Underground Environments
Shengkang Chen, Matthew J. O'Brien, Fletcher Talbot, Jason Williams, Brendan Tidd, Alex Pitt, Ronald C. Arkin
Abstract
Leveraging both the autonomy of robots and the expert knowledge of humans can enable a multi-robot system to complete missions in challenging environments with a high degree of adaptivity and robustness. This paper proposes a multi-modal task-based graphical user interface for controlling a heterogeneous multi-robot team. The core of the interface is an integrated multi-robot task allocation system to allow the user to encode his/her intents to guide the heterogeneous multi-robot team. The design of the interface aims to provide the human operator continuous situational awareness and effective control for rapid decision-making in time-critical missions. Team CSIRO Data61 came in second place utilizing this interface for the DARPA Subterranean (SubT) Challenge. The ideas used for this user interface can apply to other multi-robot applications.
BibTeX
@inproceedings{iros2022_multimodaluserin,
title = {Multi-modal User Interface for Multi-robot Control in Underground Environments},
author = {Shengkang Chen and Matthew J. O'Brien and Fletcher Talbot and Jason Williams and Brendan Tidd and Alex Pitt and Ronald C. Arkin},
booktitle = {IROS 2022},
year = {2022}
}