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Team CERBERUS Wins the DARPA Subterranean Challenge 

Robotic Systems Lab: Legged Robotics at ETH Zürich
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This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with the vision to facilitate the novel technologies necessary to reliably explore diverse underground environments despite the grueling challenges they present for robotic autonomy. Due to their geometric complexity, degraded perceptual conditions combined with lack of GPS support, austere navigation conditions, and denied communications, subterranean settings render autonomous operations particularly demanding. In response to this challenge, we developed the CERBERUS system which exploits the synergy of legged and flying robots, coupled with robust control especially for overcoming perilous terrain, multi-modal and multi-robot perception for localization and mapping in conditions of sensor degradation, and resilient autonomy through unified exploration path planning and local motion planning that reflects robot-specific limitations. Based on its ability to explore diverse underground environments and its high-level command and control by a single human supervisor, CERBERUS demonstrated efficient exploration, reliable detection of objects of interest, and accurate mapping. In this article, we report results from both the preliminary runs and the final Prize Round of the DARPA Subterranean Challenge, and discuss highlights and challenges faced, alongside lessons learned for the benefit of the community.
Team Website: www.subt-cerbe...

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27 авг 2024

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Комментарии : 6   
@TheClockworkKid320
@TheClockworkKid320 2 года назад
Have been following you guys for a while and your works are so inspiring! Hope I can one day join your research team and contribute 😁
@naclandlux
@naclandlux Год назад
Congratulations!
@robintomar3097
@robintomar3097 2 года назад
What kind of methods were used to track the odometry of the robot ? since the environment seems very unstructured and random , positioning accuracy should degrade over time. But i guess the artifacts positions were to be reported within 5 m of accuracy … how did you guys managed that?
@marcotranzatto5538
@marcotranzatto5538 2 года назад
Thanks for your interest! You can find more details about our SLAM approach and many more details in this article released just a few weeks ago: www.science.org/doi/10.1126/scirobotics.abp9742
@robintomar3097
@robintomar3097 2 года назад
@@marcotranzatto5538 thanks for the pointer. Already going through that document. Quite extensive information in there.
@abidshahriar7095
@abidshahriar7095 Год назад
is this completion valid for international university student team?
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