The kinematic features of a centaur-type humanoid platform, combined with a powerful actuation, enable the experimentation of a variety of agile and dynamic motions. However, the higher number of degrees-of-freedom and the increased weight of the system, compared to the bipedal and quadrupedal counterparts, pose significant research challenges in terms of computational load and real implementation. To this end, this work presents a control architecture to perform agile actions, conceived for torque-controlled platforms, which decouples for computational purposes offline optimal control planning of lower-body primitives, based on a template kinematic model, and online control of the upper-body motion to maintain balance. Three stabilizing strategies are presented, whose performance is compared in two types of simulated jumps, while experimental validation is performed on a half-squat jump using the CENTAURO robot.
Robots with Attitude: Singularity-Free Quaternion-Based Model-Predictive Control for Agile Legged Robots
Center for Robotics and Biosystems, Northwestern University（西北大学机器人与生物系统中心）；Robotics Institute, Carnegie Mellon University（卡内基梅隆大学机器人研究所）；Department of Mechanical Engineering, Carnegie Mellon University（卡内基梅隆大学机械工程系）
HUSKY: Humanoid Skateboarding System via Physics-Aware Whole-Body Control
Institute of Artificial Intelligence (TeleAI), China Telecom（人工智能研究院（TeleAI），中国电信）；The University of Hong Kong（香港大学）；University of Science and Technology of China（中国科学技术大学）；ShanghaiTech University（上海科技大学）
StyleLoco: Generative Adversarial Distillation for Natural Humanoid Robot Locomotion
National Key Laboratory of General Artificial Intelligence, BIGAI（通用人工智能国家重点实验室，BIGAI）；School of Control Science and Engineering, Shandong University（山东大学控制科学与工程学院）；Huazhong University of Science and Technology（华中科技大学）
A 3-Step Optimization Framework with Hybrid Models for a Humanoid Robot's Jump Motion
Beijing Institute of Technology（北京理工大学）；Intelligent Robotics Institute（智能机器人研究所）；School of Mechatronical Engineering（机电工程学院）；International Joint Research Laboratory of Biomimetic Robots and Systems, Ministry of Education（仿生机器人与系统国际联合研究实验室（教育部））
RPG: Robust Policy Gating for Smooth Multi-Skill Transitions in Humanoid Fighting
Center for Artificial Intelligence and Robotics, Shenzhen International Graduate School, Tsinghua University（人工智能与机器人中心，深圳国际研究生院，清华大学）；Shanghai AI Laboratory（上海人工智能实验室）；Northwestern Polytechnical University（西北工业大学）；Shanghai Jiao Tong University（上海交通大学）
TAGA: Terrain-aware Active Gaze Learning for Generalizable Agile Humanoid Locomotion
MarmotLab, National University of Singapore（马尔莫实验室，新加坡国立大学）；Center of X-Mechanics, Zhejiang University（浙大X力学中心）；South China University of Technology（华南理工大学）
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）
Humanoid robots are increasingly demanded to operate in interactive and human-surrounded environments while achieving sophisticated locomotion and manipulation tasks. To accomplish these tasks, roboticists unremittingly seek for advanced methods that generate whole-body coordination behaviors and meanwhile fulfill various planning and control objectives. Undoubtedly, these goals pose fundamental challenges to the robotics and control community. To take an incremental step towards reducing the performance gap between theoretical foundations and real implementations, we present a planning and co…
A Comparative Study of Floating-Base Space Parameterizations for Agile Whole-Body Motion Planning
Laboratory of Automation and Robotics (LAR) in the Department of Electrical & Computer Engineering, University of Patras（帕尔蒂亚大学电气与计算机工程系自动化与机器人实验室）；Archimedes/Athena RC（阿基米德/雅典娜研究中心）；Athena - Research and Innovation Center in Information, Communication and Knowledge Technologies（雅典娜信息、通信和知识技术研究与创新中心）
LeVERB: Humanoid Whole-Body Control with Latent Vision-Language Instruction
University of California Berkeley（加州大学伯克利分校）；Norwegian University of Science and Technology（挪威科学与技术大学）；Simon Fraser University（西蒙弗雷泽大学）；Carnegie Mellon University（卡内基梅隆大学）
BeamDojo: Learning Agile Humanoid Locomotion on Sparse Footholds
Shanghai AI Laboratory（上海人工智能实验室）；Shanghai Jiao Tong University（上海交通大学）；Zhejiang University（浙江大学）；The University of Hong Kong（香港大学）；The Chinese University of Hong Kong（香港中文大学）
PhyGile: Physics-Prefix Guided Motion Generation for Agile General Humanoid Motion Tracking
Northwestern Polytechnical University（西北工业大学）；Shanghai AI Laboratory（上海人工智能实验室）；University of Science and Technology of China（中国科学技术大学）；Tsinghua University（清华大学）；Fudan University（复旦大学）；ByteDance（字节跳动）；Northeastern University（东北大学）
Politecnico di Milano（米兰理工大学）；Istituto Italiano di Tecnologia（意大利技术研究院）
Hybrid wheeled-legged locomotion is a navigation paradigm only recently opened up by novel robotic designs,e.g. the centaur-type humanoid CENTAURO [1] or the quadruped ANYmal [2] in its configuration featuring non-steerable wheels. The term Hybrid Locomotion is hereafter used to indicate a particular type of locomotion, achieved with simultaneous and coordinate use of legs and wheels,see Fig. 1. Such choice stems at the intersection between legged locomotion and the simpler wheeled navigation, in order to get the best from both techniques: agility and ability to traverse uneven terrains from t…
Reinforcement learning has shown great promise for synthesizing realistic human behaviors by learning humanoid control policies from motion capture data. However, it is still very challenging to reproduce sophisticated human skills like ballet dance, or to stably imitate long-term human behaviors with complex transitions. The main difficulty lies in the dynamics mismatch between the humanoid model and real humans. That is, motions of real humans may not be physically possible for the humanoid model. To overcome the dynamics mismatch, we propose a novel approach, residual force control (RFC), t…
