Team CERBERUS Wins the DARPA Subterranean Challenge @autonomousrobotslab
Team CERBERUS Wins the DARPA Subterranean Challenge  @autonomousrobotslab
Uploaded June 2022 | Updated September 2026, 3 weeks ago
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: subt-cerberus.org
Team CERBERUS Wins the DARPA Subterranean ChallengeRRTOT: Optimal Inspection Path-PlanningCollaborative Exploration with a Marsupial Ground-Aerial Robot TeamAutonomous Aerial Robotic Exploration and Mapping of a Railroad Tunnel in Degraded Visual ConditionsIEEE ICRA 2019 Workshop on The Future of Aerial Robotics: Challenges & OpportunitiesReinforcement Learning for Collision-free Flight Exploiting Deep Collision EncodingCOHORT-GBPlanner2 Interfacing for Teamed Exploration - How It WorksTeam CERBERUS: DARPA Subterranean Challenge Technical Approach and Lessons LearnedNSF RET Site on Robotics & Big Data for Smart CitiesOnline Refractive Camera Model Calibration in Visual Inertial OdometryDARPA SubT Urban Circuit: Collision-tolerant Exploration of Staircases using Aerial RobotsIROS2022 Talk: Risk-Aware Motion Planning for Collision-Tolerant Aerial Robots s.t. Uncertainty
Kostas Alexis |

Team CERBERUS Wins the DARPA Subterranean Challenge

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