System for multi-robotic exploration of underground environments CTU-CRAS-NORLAB in the DARPA Subterranean Challenge
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Abstract (arXiv)
We present a field report of CTU-CRAS-NORLAB team from the Subterranean Challenge (SubT) organised by the Defense Advanced Research Projects Agency (DARPA). The contest seeks to advance technologies that would improve the safety and efficiency of search-and-rescue operations in GPS-denied environments. During the contest rounds, teams of mobile robots have to find specific objects while operating in environments with limited radio communication, e.g. mining tunnels, underground stations or natural caverns. We present a heterogeneous exploration robotic system of the CTU-CRAS-NORLAB team, which achieved the third rank at the SubT Tunnel and Urban Circuit rounds and surpassed the performance of all other non-DARPA-funded teams. The field report describes the team's hardware, sensors, algorithms and strategies, and discusses the lessons learned by participating at the DARPA SubT contest.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Oct 2021.
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Citing papers per year: 2022: 3; 2023: 1; 2024: 1.
5 papers.
- 2022Federated Reinforcement Learning for Collective Navigation of Robotic Swarmscited by 7
- 2024STAGE: Scalable and Traversability-Aware Graph based Exploration Planner for Dynamically Varying Environmentscited by 3
- 2022Copiloting Autonomous Multi-Robot Missions: A Game-inspired Supervisory Control Interfacecited by 1
- 2022Virtual Reality via Object Pose Estimation and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilitiescited by 1
- 2023Multimodal Dataset from Harsh Sub-Terranean Environment with Aerosol Particles for Frontier Explorationcited by 1
- 2024STAGE: Scalable and Traversability-Aware Graph based Exploration Planner for Dynamically Varying Environments4 Feb 2024
- 2023Multimodal Dataset from Harsh Sub-Terranean Environment with Aerosol Particles for Frontier Exploration27 Apr 2023
- 2022Virtual Reality via Object Pose Estimation and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilities18 Oct 2022
- 2022Copiloting Autonomous Multi-Robot Missions: A Game-inspired Supervisory Control Interface13 Apr 2022
- 2022Federated Reinforcement Learning for Collective Navigation of Robotic Swarms2 Feb 2022