Heterogeneous Ground and Air Platforms, Homogeneous Sensing: Team CSIRO Data61's Approach to the DARPA Subterranean Challenge
Nicolas Hudson, Fletcher Talbot, Mark Cox, Jason Williams, Thomas Hines, Alex Pitt, Brett Wood, Dennis Frousheger, Katrina Lo Surdo, Thomas Molnar, Ryan Steindl, Matt Wildie, Inkyu Sa, Navinda Kottege, Kazys Stepanas, Emili Hernández, Gavin Catt, William Docherty, Brendan Tidd, Benjamin Tam
- Year
- 2022
- Citations
- 97
- Access
- Open access
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
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002