Heterogeneous Ground and Air Platforms, Homogeneous Sensing: Team CSIRO Data61's Approach to the DARPA Subterranean Challenge
CSIRO（联邦科学与工业研究组织）；Emesent；Georgia Tech（佐治亚理工学院）
Nicolas Hudson, Fletcher Talbot, Mark Cox, Jason Williams, Thomas Hines, Alex Pitt, Brett Wood, Dennis Frousheger, Katrina Lo Surdo, Thomas Molnar, Ryan Steindl… 展开作者
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 Hernandez, Gavin Catt, William Docherty, Brendan Tidd, Benjamin Tam, Simon Murrell, Mitchell Bessell, Lauren Hanson, Lachlan Tychsen-Smith, Hajime Suzuki, Leslie Overs, Farid Kendoul, Glenn Wagner, Duncan Palmer, Peter Milani, Matthew O'Brien, Shu Jiang, Shengkang Chen, Ronald C. Arkin
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 utilised, which is leveraged to obtain a decentralised multi-agent SLAM solution on each platform (both ground agents and UAVs) using peer-to-peer communications. This 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 OzBot Titan ground robot and an Emesent Hovermap UAV, supplemented by smaller tracked or legged ground robots. The ground agents use a common CatPack perception module, which allowed reuse of the perception and autonomy stack across all ground agents with minimal adaptation.
LAMP: Large-Scale Autonomous Mapping and Positioning for Exploration of Perceptually-Degraded Subterranean Environments
NASA Jet Propulsion Laboratory - California Institute of Technology（美国国家航空航天局喷气推进实验室 - 加州理工学院）；Department of Aeronautics and Astronautics, Massachusetts Institute of Technology（麻省理工学院航空航天系）；Department of Computer Science, University of Southern California（南加州大学计算机科学系）；Aptiv（阿普提夫公司 (Aptiv)）
CompSLAM: Complementary Hierarchical Multi-Modal Localization and Mapping for Robot Autonomy in Underground Environments
Jet Propulsion Lab, California Institute of Technology, USA（喷气推进实验室，加州理工学院，美国）；Division of Robotics, Perception, and Learning, KTH Royal Institute of Technology, Sweden（机器人、感知与学习系，皇家理工学院，瑞典）；Autonomous Systems Lab, ETH Zürich, Switzerland（自主系统实验室，苏黎世联邦理工学院，瑞士）；Robotic Systems Lab, ETH Zürich, Switzerland（机器人系统实验室，苏黎世联邦理工学院，瑞士）；Autonomous Robots Lab, NTNU, Trondheim, Norway（自主机器人实验室，挪威特罗姆瑟大学，挪威）
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
ETH Zurich（苏黎世联邦理工学院）；University of Nevada, Reno（内华达大学雷诺分校）；Norwegian University of Science and Technology（挪威科技大学）；Flyability（Flyability公司）；Oxford Robotics Institute, University of Oxford（牛津大学牛津机器人研究所）
Heterogeneous Ground-Air Autonomous Vehicle Networking in Austere Environments: Practical Implementation of a Mesh Network in the DARPA Subterranean Challenge
University of Colorado Boulder（科罗拉多大学博尔德分校）；University of California Santa Cruz（加州大学圣克鲁兹分校）
Human-Robot Team Performance Compared to Full Robot Autonomy in 16 Real-World Search and Rescue Missions: Adaptation of the DARPA Subterranean Challenge
NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge
NASA Jet Propulsion Laboratory（美国国家航空航天局喷气推进实验室）；California Institute of Technology（加州理工学院）；Massachusetts Institute of Technology（麻省理工学院）；University of Southern California（南加州大学）；University of Colorado Boulder（科罗拉多大学博尔德分校）
LOCUS 2.0: Robust and Computationally Efficient Lidar Odometry for Real-Time Underground 3D Mapping
NASA Jet Propulsion Laboratory, California Institute of Technology（美国国家航空航天局喷气推进实验室，加州理工学院）；University of Bonn（波恩大学）；Polytechnic University of Bari（巴里理工大学）；Massachusetts Institute of Technology（麻省理工学院）
激光雷达测距作为一种鲁棒的自主机器人定位方法，在复杂的GNSS拒绝环境中运行，引起了相当大的关注。然而，由于自主操作所需的板载计算和存储器资源的限制，在大规模环境中的异构平台上实现可靠和高效的性能仍然是一个开放的挑战。在这项工作中，我们提出了LOCUS 2.0，一个强大的和计算效率高的\lidar里程计系统的实时的【形】地下三维映射。LOCUS 2.0包括一个新的基于法线的\morrell{Generalized Iterative Closest Point (GICP)}公式，它减少了点云对齐的计算时间，一个自适应体素网格过滤器，它保持了所需的计算负载，而不管环境的几何形状，和一个滑动窗口地图的方法，限制了内存消耗。所提出的方法被证明是适合部署在异构机器人平台上参与大规模的探索下严重的计算和内存限制。我们展示了LOCUS 2.0，这是CoSTAR团队进入DARPA地下挑战赛的一个关键因素，在各种地下场景中。我们将LOCUS 2.0作为开源库发布，并在具有挑战性的大规模地下环境中发布基于\lidar的里程数据集。该数据集的特点是在多种环境中的腿和轮式平台，包括雾，灰尘，黑暗和几何退化的环境，总的$11~h$的操作和$16~km$的行驶距离。
LAMP 2.0: A Robust Multi-Robot SLAM System for Operation in Challenging Large-Scale Underground Environments
Massachusetts Institute of Technology（麻省理工学院）；NASA Jet Propulsion Laboratory – California Institute of Technology（美国国家航空航天局喷气推进实验室——加州理工学院）；University of Southern California（南加州大学）；University of Bonn（波恩大学）；Polytechnic University of Bari（巴里理工大学）；Bangladesh University of Engineering and Technology（孟加拉国工程技术大学）
Multi-Agent Autonomy: Advancements and Challenges in Subterranean Exploration
University of Colorado Boulder（科罗拉多大学博尔德分校）；University of California Santa Cruz（加利福尼亚大学圣克鲁兹分校）；Aerospace Engineering Sciences（航空航天工程科学（注：此处为系/专业，按要求不提取，仅保留大学/学院级别机构））；Mechanical Engineering（机械工程（注：此处为系/专业，按要求不提取，仅保留大学/学院级别机构））；Computer Science（计算机科学（注：此处为系/专业，按要求不提取，仅保留大学/学院级别机构））；Electrical & Computer Engineering（电气与计算机工程（注：此处为系/专业，按要求不提取，仅保留大学/学院级别机构））
An Addendum to NeBula: Towards Extending TEAM CoSTAR's Solution to Larger Scale Environments
NASA Jet Propulsion Laboratory, California Institute of Technology（美国国家航空航天局喷气推进实验室、加州理工学院）；California Institute of Technology（加州理工学院）；Korea Advanced Institute of Science and Technology（韩国科学技术院）；Massachusetts Institute of Technology（麻省理工学院）；Stanford University（斯坦福大学）；California State University, Northridge（加州州立大学北岭分校）；Polytechnic University of Bari（巴里理工大学）；Cornell University（康奈尔大学）；McGill University（麦吉尔大学）；Blue Marble Space Institute of Science（蓝 marble 太空科学研究所）
Copiloting Autonomous Multi-Robot Missions: A Game-inspired Supervisory Control Interface
Polytechnique Montreal（蒙特利尔理工学院）；NASA Jet Propulsion Laboratory, California Institute of Technology（美国国家航空航天局喷气推进实验室，加州理工学院）；University of Southern California（南加州大学）；University of California, Riverside（加州大学河滨分校）
Hybrid Aerial-Ground Vehicle Autonomy in GPS-denied Environments
School of Aerospace, Mechanical and Mechatronic Engineering（航空航天、机械与机电工程学院）；The University of Sydney（悉尼大学）；Jet Propulsion Laboratory, California Institute of Technology（加州理工学院喷气推进实验室）
