Geometry of contact: contact planning for multi-legged robots via spin models duality
Georgia Institute of Technology（佐治亚理工学院）；NSF AI Institute for Artificial Intelligence and Fundamental Interactions（美国国家科学基金会人工智能与基本相互作用人工智能研究所）；Massachusetts Institute of Technology（麻省理工学院）；Harvard University（哈佛大学）
Baxi Chong, Di Luo, Tianyu Wang, Gabriel Margolis, Juntao He, Pulkit Agrawal, Marin Soljačić, Daniel I. Goldman
Contact planning is crucial in locomoting systems.Specifically, appropriate contact planning can enable versatile behaviors (e.g., sidewinding in limbless locomotors) and facilitate speed-dependent gait transitions (e.g., walk-trot-gallop in quadrupedal locomotors). The challenges of contact planning include determining not only the sequence by which contact is made and broken between the locomotor and the environments, but also the sequence of internal shape changes (e.g., body bending and limb shoulder joint oscillation). Most state-of-art contact planning algorithms focused on conventional robots (e.g.biped and quadruped) and conventional tasks (e.g. forward locomotion), and there is a lack of study on general contact planning in multi-legged robots. In this paper, we show that using geometric mechanics framework, we can obtain the global optimal contact sequence given the internal shape changes sequence. Therefore, we simplify the contact planning problem to a graph optimization problem to identify the internal shape changes. Taking advantages of the spatio-temporal symmetry in locomotion, we map the graph optimization problem to special cases of spin models, which allows us to obtain the global optima in polynomial time. We apply our approach to develop new forward and sidewinding behaviors in a hexapod and a 12-legged centipede. We verify our predictions using numerical and robophysical models, and obtain novel and effective locomotion behaviors.
Angular Divergent Component of Motion: A step towards planning Spatial DCM Objectives for Legged Robots
Virginia Polytechnic Institute and State University（弗吉尼亚理工学院暨州立大学）；Institute of Robotics and Mechatronics, German Aerospace Center (DLR)（德国航空航天中心机器人与机电一体化研究所）；Florida Institute for Human and Machine Cognition (IHMC)（佛罗里达人机认知研究所）
ViTAL: Vision-Based Terrain-Aware Locomotion for Legged Robots
Istituto Italiano di Tecnologia (IIT)（意大利理工学院）
这项工作是基于视觉的规划策略的足式机器人分离到立足点选择和姿势适应运动规划。目前的姿态自适应策略优化机器人的身体姿势相对于给定的立足点。如果未到达这些立足点，则机器人可能最终处于没有可到达的安全立足点的状态。因此，我们提出了一个基于视觉的地形感知运动（ViTAL）的战略，包括新的姿态适应和立足点选择算法。ViTAL在姿势适应中引入了一种不同的范例，该范例不优化相对于给定立足点的身体姿势，而是最大化腿部到达安全立足点的机会的身体姿势。ViTAL根据机器人的能力和地形感知能力来规划立足点和姿势。我们使用90 kg HyQ和140 kg HyQReal四足机器人来验证ViTAL，并表明它们能够以不同的速度和步态爬上各种障碍物，包括楼梯，间隙和粗糙的地形。我们比较ViTAL与基线策略，选择机器人姿势的基础上，给定选定的立足点，并显示ViTAL优于基线。
Tactile sensing enables vertical obstacle negotiation for elongate many-legged robots
Institute for Robotics and Intelligent Machines（机器人与智能机器研究所）；Georgia Institute of Technology（佐治亚理工学院）；School of Physics（物理系）；School of Mechanical Engineering（机械工程系）；College of Computing（计算学院）
Autonomous Forest Inventory with Legged Robots: System Design and Field Deployment
University of Oxford（牛津大学）；Oxford Robotics Institute（牛津机器人研究所）；Technical University of Munich（慕尼黑工业大学）；ETH Zurich（苏黎世联邦理工学院）；Robotic Systems Lab（机器人系统实验室）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）
Istituto Italiano di Tecnologia（意大利技术研究院）；Università degli Studi di Genova（热那亚大学）；Swiss Federal Institute of Technology at Lausanne（洛桑联邦理工学院）；University of Texas（德克萨斯大学）；University of Naples Federico II（那不勒斯费德里科二世大学）
Building Forest Inventories with Autonomous Legged Robots -- System, Lessons, and Challenges Ahead
Oxford Robotics Institute, Department of Engineering Science, University of Oxford, Oxford, UK（牛津大学机器人研究所、工程科学系、牛津大学）；Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland（机械与过程工程系、苏黎世联邦理工学院）；Max Planck Institute for Intelligent Systems, Tübingen, Germany（智能系统马克斯·普朗克研究所、图宾根德国）；Technical University of Munich, Munich, Germany（慕尼黑技术大学）
WAVE-Go: World-Model Navigation with Adaptive Execution for Wheel-Legged Robots
Beijing Institute of Technology（北京理工大学）；The University of Hong Kong（香港大学）；GAC R&D Center（广汽研究院）；LimX Dynamics；Beijing Academy of Artificial Intelligence (BAAI)（北京人工智能研究院）
Efficient Path Planning and Tracking for Multi-Modal Legged-Aerial Locomotion Using Integrated Probabilistic Road Maps (PRM) and Reference Governors (RG)
California Institute of Technology（加州理工学院）；Ecole Polytechnique Fédérale de Lausanne（洛桑联邦理工学院）；Northeastern University（东北大学）
GeCCo -- a Generalist Contact-Conditioned Policy for Loco-Manipulation Skills on Legged Robots
Dynamic Robot Systems Group, Oxford Robotics Institute, University of Oxford（牛津大学机器人研究所动态机器人系统组）；Sony AI（索尼人工智能）；Dyson Institute of Engineering and Technology（戴森工程与技术研究所）
Bi-Level Optimization for Contact and Motion Planning in Rope-Assisted Legged Robots
Dipartimento di Ingegneria e Scienza dell’Informazione (DISI), University of Trento（工程与信息科学系（DISI），特伦托大学）；Inria, Université de Lorraine, CNRS（法国国家信息与自动化技术研究院（Inria）、洛林大学、法国国家科学研究中心（CNRS））
Agile asymmetric multi-legged locomotion: contact planning via geometric mechanics and spin model duality
Department of Mechanical Engineering, Pennsylvania State University（宾夕法尼亚州立大学机械工程系）；MIT Improbable AI Lab, Maschusetts Institute of Technology（麻省理工学院Improbable AI实验室）；Department of Physics, Georgia Institute of Technology（佐治亚理工学院物理系）；Department of Physics, Tsinghua University（清华大学物理系）
