In this paper, we develop an online active mapping system to enable a quadruped robot to autonomously survey large physical structures. We describe the perception, planning and control modules needed to scan and reconstruct an object of interest, without requiring a prior model. The system builds a voxel representation of the object, and iteratively determines the Next-Best-View (NBV) to extend the representation, according to both the reconstruction itself and to avoid collisions with the environment. By computing the expected information gain of a set of candidate scan locations sampled on the as-sensed terrain map, as well as the cost of reaching these candidates, the robot decides the NBV for further exploration. The robot plans an optimal path towards the NBV, avoiding obstacles and un-traversable terrain. Experimental results on both simulated and real-world environments show the capability and efficiency of our system. Finally we present a full system demonstration on the real robot, the ANYbotics ANYmal, autonomously reconstructing a building facade and an industrial structure.
Multi-Task Learning of Active Fault-Tolerant Controller for Leg Failures in Quadruped robots
Academy for Engineering and Technology, Fudan University（复旦大学工程与技术学院）；Beijing Jingcheng Zhitong Robotics Technology Co.（北京京城智通机器人科技有限公司）；Ji Hua Laboratory（季华实验室）；Engineering Research Center of AI and Robotics（人工智能与机器人工程研究中心）
Design and Control of the "QuadBoat": A Quadruped Surface Vehicle for Drowning Rescue
Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS)（深圳社会人工智能与机器人研究所）；The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen)（香港中文大学（深圳））；Stevens Institute of Technology（史蒂文斯理工学院）
Autonomous UAV-Quadruped Docking in Complex Terrains via Active Posture Alignment and Constraint-Aware Control
College of Electronics and Information Engineering, Tongji University（同济大学电子与信息工程学院）；Frontiers Science Center for Intelligent Autonomous Systems, Shanghai（上海智能自主系统前沿科学中心）；School of Logistics Engineering, Shanghai Maritime University（上海 Maritime University物流工程学院）；State Key Laboratory of Autonomous Intelligent Unmanned Systems, Shanghai（上海自主智能无人系统国家重点实验室）
A Deployable Bio-inspired Compliant Leg Design for Enhanced Leaping in Quadruped Robots
Department of Mechatronics and Robotics, Xi’an Jiaotong-Liverpool University（机电一体化与机器人系，西安交通大学-利物浦大学）；Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign（机械科学与工程系，伊利诺伊大学厄巴纳-香槟分校）
Kinematics-Aware Multi-Policy Reinforcement Learning for Force-Capable Humanoid Loco-Manipulation
the Robot and Artificial Intellifence Lab, College of Electronic and Information Engineering, Tongji University, Shanghai 201804, China（机器人与人工智能实验室，电子与信息工程学院，同济大学，上海）；State Key Laboratory of Autonomous Intelligent Unmanned System(Tongji University), Shanghai, China（自主智能无人系统国家重点实验室（同济大学），上海）
ETH Zurich（苏黎世联邦理工学院）；Sony Group Corporation（索尼集团公司）；National University of Singapore（新加坡国立大学）；Nara Institute of Science and Technology（奈良科学技术研究所）；The University of Tokyo（东京大学）
Pickalo: Leveraging 6D Pose Estimation for Low-Cost Industrial Bin Picking
MESH Facility (formerly iCub Tech), Istituto Italiano di Tecnologia（意大利技术研究院MESH设施（原iCub Tech））；AMI laboratory, Istituto Italiano di Tecnologia（意大利技术研究院AMI实验室）；Institut des Systèmes Intelligents et de Robotique (ISIR)（智能系统与机器人研究所（ISIR））；Generative Bionics（Generative Bionics公司）；Camozzi Automation SpA（Camozzi自动化股份公司）
Laboratoire des Sciences du Numérique de Nantes (LS2N), CNRS（劳伦斯数字科学南特实验室（LS2N），CNRS）；Ecole Centrale de Nantes (ECN)（南特中央理工学院（ECN））；University of Genoa（热那亚大学）
