Navigating in search and rescue environments is challenging, since a variety of terrains has to be considered. Hybrid driving-stepping locomotion, as provided by our robot Momaro, is a promising approach. Similar to other locomotion methods, it incorporates many degrees of freedom---offering high flexibility but making planning computationally expensive for larger environments.
We propose a navigation planning method, which unifies different levels of representation in a single planner. In the vicinity of the robot, it provides plans with a fine resolution and a high robot state dimensionality. With increasing distance from the robot, plans become coarser and the robot state dimensionality decreases. We compensate this loss of information by enriching coarser representations with additional semantics. Experiments show that the proposed planner provides plans for large, challenging scenarios in feasible time.
Omnidirectional Humanoid Locomotion on Stairs via Unsafe Stepping Penalty and Sparse LiDAR Elevation Mapping
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（华中科技大学人工智能与自动化学院）；State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology（华中科技大学智能制造装备技术国家重点实验室）；School of Mechanical Science and Engineering, Huazhong University of Science and Technology（华中科技大学机械科学与工程学院）
Walk the PLANC: Physics-Guided RL for Agile Humanoid Locomotion on Constrained Footholds
Department of Mechanical and Civil Engineering, California Institute of Technology（机械与土木工程系，加州理工学院）；Department of Computing and Mathematical Sciences, California Institute of Technology（计算与数学科学系，加州理工学院）
Diffusion-based learning of contact plans for agile locomotion
Munich Institute of Robotics and Machine Intelligence, Technical University of Munich, Germany（慕尼黑机器人与机器智能研究所，慕尼黑技术大学）；Tandon School of Engineering, New York University, USA（纽约大学土曼工学院）；Max-Planck Institute for Intelligent Systems, Tübingen, Germany（马克斯·普朗克智能系统研究所，图宾根）
Terrain-Aware Quadrupedal Locomotion via Reinforcement Learning
Tencent Robotics X（腾讯Robotics X）；The Chinese University of Hong Kong（香港中文大学）；Southern University of Science and Technology（南方科技大学）；University of Alberta（阿尔伯塔大学）
Adaptive Step Duration for Accurate Foot Placement: Achieving Robust Bipedal Locomotion on Terrains with Restricted Footholds
Mechanical and Aerospace Engineering, The Ohio State University（机械与航空航天工程系，俄亥俄州立大学）；Electrical and Computer Engineering, The Ohio State University（电气与计算机工程系，俄亥俄州立大学）
Gallant: Voxel Grid-based Humanoid Locomotion and Local-navigation across 3D Constrained Terrains
Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；The Chinese University of Hong Kong（香港中文大学）；University of Science and Technology of China（中国科学技术大学）；University of Tokyo（东京大学）；Shanghai Jiaotong University（上海交通大学）
Nonlinear Model Predictive Control for Robust Bipedal Locomotion: Exploring Angular Momentum and CoM Height Changes
School of Power and Mechanical Engineering, Wuhan University（武汉大学动力与机械学院）；Shenzhen Institute of Artificial Intelligence and Robotics for Society（深圳人工智能与机器人研究院）；School of Mechanical Engineering, University of Leeds（利兹大学机械工程学院）；School of Informatics, The University of Edinburgh（爱丁堡大学信息学院）；Humanoid and Human Centered Mechatronics Research Line, Istituto Italiano di Tecnologia（意大利技术研究院人形与以人为中心的机电一体化研究线）
Watch Your Step: Learning Semantically-Guided Locomotion in Cluttered Environment
School of Electrical and Electronic Engineering, Nanyang Technological University（南洋理工大学电气与电子工程学院）；School of Mechanical and Mining Engineering, The University of Queensland（昆士兰大学机械与采矿工程学院）
Gait-Adaptive Perceptive Humanoid Locomotion with Real-Time Under-Base Terrain Reconstruction
Department of Electronic Engineering and Information Science (EEIS), University of Science and Technology of China（电子工程与信息科学系，中国科学技术大学）；LimX Dynamics（LimX动力学）；Hong Kong University of Science and Technology（香港科技大学）；School of Mechanics Engineering, Harbin Institute of Technology (HIT)（机械工程学院，哈尔滨工业大学）；Department of Computing, The Hong Kong Polytechnic University（计算学院，香港理工大学）；Zhejiang University-University of Illinois Urbana-Champaign Institute (ZJUI)（浙江大学-伊利诺伊大学厄巴纳-香槟分校联合研究所）
Time to Play: Simulating Early-Life Animal Dynamics Enhances Robotics Locomotion Discovery
Adaptive & Intelligent Robotics Lab, Imperial College London, United Kingdom（智能适应机器人实验室，帝国理工学院伦敦分校）；Evolutionary Biomechanics Laboratory, Imperial College London, United Kingdom（进化生物力学实验室，帝国理工学院伦敦分校）
Unleashing the Agility of Wheeled-Legged Robots for High-Dynamic Reflexive Obstacle Evasion
School of Mechanical Engineering, Tianjin University（天津大学机械工程学院）；School of Computing, National University of Singapore（新加坡国立大学计算机学院）；Beijing Zhongguancun Academy（北京中关村学院）；DeepRobotics（深睿科技）
Learning Linear Policies for Robust Bipedal Locomotion on Terrains with Varying Slopes
Indian Institute of Technology (BHU) Varanasi（印度理工学院（巴纳拉斯印度教大学）瓦拉纳西分校）；Indian Institute of Technology Roorkee（印度理工学院鲁尔基分校）；Ohio State University（俄亥俄州立大学）；Indian Institute of Science（印度科学学院）
Human-Centered Development of Guide Dog Robots: Quiet and Stable Locomotion Control
Department of Computer Science, University of Texas at Austin（德克萨斯大学奥斯汀分校计算机科学系）；School of Computing and Information Science, University of Maine（缅因大学计算与信息科学学院）
Robust Humanoid Walking on Compliant and Uneven Terrain with Deep Reinforcement Learning
CNRS-AIST JRL (Joint Robotics Laboratory) IRL, National Institute of Advanced Industrial Science and Technology (AIST), Japan（日本国家先进工业科学与技术研究院（AIST））；University of Tsukuba（筑波大学）；Department of Computer Science, Stanford University（斯坦福大学计算机科学系）
