Heterogeneous Ground and Air Platforms, Homogeneous Sensing: Team CSIRO Data61’s Approach to the DARPA Subterranean Challenge

Author:

Hudson NicolasORCID,Talbot FletcherORCID,Cox MarkORCID,Williams JasonORCID,Hines ThomasORCID,Pitt AlexORCID,Wood BrettORCID,Frousheger DennisORCID,Lo Surdo KatrinaORCID,Molnar ThomasORCID,Steindl RyanORCID,Wildie MattORCID,Sa InkyuORCID,Kottege NavindaORCID,Stepanas KazysORCID,Hernandez EmiliORCID,Catt GavinORCID,Docherty WilliamORCID,Tidd BrendanORCID,Tam BenjaminORCID,Murrell SimonORCID,Bessell MitchellORCID,Hanson LaurenORCID,Tychsen-Smith LachlanORCID,Suzuki HajimeORCID,Overs LeslieORCID,Kendoul FaridORCID,Wagner GlennORCID,Palmer DuncanORCID,Milani PeterORCID,O’Brien MatthewORCID,Jiang ShuORCID,Chen ShengkangORCID,Arkin RonaldORCID

Abstract

Heterogeneous teams of robots, leveraging a balance between autonomy and human interaction, bring powerful capabilities to the problem of exploring dangerous, unstructured subterranean environments. Here we describe the solution developed by Team CSIRO Data61, consisting of CSIRO, Emesent, and Georgia Tech, during the DARPA Subterranean Challenge. These presented systems were fielded in the Tunnel Circuit in August 2019, the Urban Circuit in February 2020, and in our own Cave event, conducted in September 2020. A unique capability of the fielded team is the homogeneous sensing of the platforms utilized, which is used to obtain a decentralized multi-agent SLAM solution on each platform (both ground agents and UAVs) using peer-to-peer communications. This approach enabled a shift in focus from constructing a pervasive communications network to relying on multi-agent autonomy, motivated by experiences in early circuit events. These experiences also showed the surprising capability of rugged tracked platforms for challenging terrain, which in turn led to the heterogeneous team structure based on a BIA5 OzBot Titan ground robot and an Emesent Hovermap UAV, supplemented by smaller tracked or legged ground robots. The ground agents use a common CatPack perception module, which allowed reuse of the perception and autonomy stack across all ground agents with minimal adaptation.

Publisher

Field Robotics Publication Society

Cited by 50 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3