DARPA Subteriterranean Challenge, DARPA, USA

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Article "The Pentagon’s $82 Million Super Bowl of Robots"
Inside a three-year competition that raises the question: How long until humans are obsolete?

by David Montgomery
November 10, 2021

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SubT finals recap and what’s next

Nov 9, 2021

We invite you to hear from the leadership of Team Explorer, the CMU DARPA Subterranean Challenge team, as they discuss the challenges, lessons learned, and the future direction these technologies are headed in. Discover opportunities the research has created and how industry can engage.

Over the past three years, some of the world's top universities have entered the DARPA Subterranean Challenge, developing technologies to map, navigate and search underground environments. Team Explorer, led by Carnegie Mellon University’s Robotics Institute faculty members Sebastian Scherer and Matt Travers, as well as Oregon State University’s Geoff Hollinger, gave a solid performance throughout the event, placing 4th place in the final leg of the competition. Notably, the team earned the distinction of having the most sectors explored.

The SubT team is happy to answer questions from the audience following the presentation.

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RI Seminar: Sebastian Scherer & Matthew Travers : Team Explorer’s Approach and Lessons Learned

Nov 20, 2021

Sebastian Scherer & Matthew Travers
Robotics Institute, Carnegie Mellon University
November 19, 2021

Resilient Exploration in SubT Environments: Team Explorer’s Approach and Lessons Learned in the Final Event

Abstract: Subterranean robot exploration is difficult with many mobility, communications, and navigation challenges that require an approach with a diverse set of systems, and reliable autonomy. While prior work has demonstrated partial successes in addressing the problem, here we convey a comprehensive approach to address the problem of subterranean exploration in a wide range of tunnel, urban, and cave environments. Our approach is driven by the themes of resiliency and modularity, and we show examples of how these themes influence the design of the different modules. In particular, we detail our approach to artifact detection, pose estimation, coordination, planning, control, and autonomy, and discuss our performance in the Final DARPA Subterranean Challenge.SS

Brief Bios:

Sebastian Scherer is an Associate Research Professor at the Robotics Institute (RI) at Carnegie Mellon University (CMU). His research focuses on enabling autonomy for unmanned rotorcraft to operate at low altitude in cluttered environments. He and His team have shown the fastest and most tested obstacle avoidance on an Yamaha RMax (2006), the first obstacle avoidance for micro aerial vehicles in natural environments (2008), and the first (2010) and fastest (2014) automatic landing zone detection and landing on a full-size helicopter. Dr. Scherer received his B.S. in Computer Science, M.S. and Ph.D. in Robotics from CMU in 2004, 2007, and 2010. He is a Siebel scholar and a recipient of multiple paper awards and nominations, including AIAA@Infotech 2010 and FSR 2013. His research has been covered by the national and internal press including IEEE Spectrum, the New Scientist, Wired, der Spiegel, and the WSJ. His work on self-landing helicopters has received the Popular Science Best of What’s New 2010 Award and in Fall 2016 he demonstrated his inspection robots to President Obama.

Matthew Travers’ research focuses on developing the intelligence necessary to enable complex platforms to autonomously interact with and perform meaningful work in complex environments. The task areas on which he is currently focusing include biologically inspired dynamic locomotion and learning, compliant manipulation for agriculture and food preparation, managing uncertainty in human-robot interaction, and field-ready search and rescue robotics. The central ideas that underlie the analytical aspects of Travers’ work are drawn from classical control theory, Bayesian inference, practical optimal control, and modern reinforcement learning.