The Strange Attractor Model of Bipedal Locomotion and its Consequences on Motor Control
School of Engineering and Informatics, University of Sussex（萨塞克斯大学工程与信息学院）；Rehabilitation Research Institute of Singapore, Nanyang Technological University（新加坡南洋理工大学新加坡康复研究院）；School of Informatics, University of Edinburgh（爱丁堡大学信息学院）；School of Electronics Engineering, Kyungpook National University（庆北国立大学电子工程学院）；Escola Politecnica da Universidade de Sao Paulo（圣保罗大学理工学院）
Carlo Tiseo, Ming Jeat Foo, Kalyana C Veluvolu, Arturo Forner-Cordero, Wei Tech Ang
尽管经过数十年的研究，关于控制人类运动的机制仍存在许多未知。现有的模型和运动控制理论只能部分捕捉这一现象。这可能是下肢康复疗法疗效降低的一个主要原因。最近，有研究提出，可以通过对吸引子动力学进行建模，利用作用在质心（CoM）上的引力，在任务空间中规划人类运动。所提出的模型将 CoM 的横向轨迹表示为在吸引子流形上传播的谐振子。然而，通过脚踝策略控制的 CoM 垂直轨迹尚未被准确捕捉。研究问题：是否可以通过引入脚踝策略的数学模型，将脚跟触地和脚尖离地策略与 CoM 运动相协调，从而提高模型精度？我们的解决方案由闭式方程组成，为 CoM、足部摆动和脚踝策略规划类人轨迹。我们通过从 12 名健康受试者在 3 种自选速度下的动作捕捉轨迹中提取运动学和姿态数据，使用我们的模型生成一个虚拟受试者来测试该模型。我们的虚拟受试者基于收集数据的平均值。模型输出显示，我们的虚拟受试者的行走轨迹特征与我们的动作捕捉数据一致。此外，数据分析表明，我们的模型像人类一样调节足部的支撑相。该模型证明运动可以被建模为吸引子动力学，证明了我们的神经系统学习的一个非线性映射的存在。它可以支持对运动运动控制的更深入调查，潜在地改善运动康复和辅助技术。
英文摘要：
Despite decades of research, the dynamic mechanisms governing human locomotion remain incompletely understood. Current motor control models only partially capture these complex dynamics, a theoretical gap that likely limits the clinical efficacy of modern lower-limb rehabilitation therapies. Recently, it has been proposed that human locomotion is planned in task-space by explicitly exploiting the gravitational pull acting on the Center of Mass (CoM). Building upon this concept, this paper presents a novel deterministic task-space planner for straight, constant-speed locomotion. Our model formulates the CoM trajectory in the transverse plane as a harmonic oscillator moving at a constant forward velocity, while demonstrating that the vertical CoM trajectory is actively regulated through localized ankle strategies. We derive closed-form equations that successfully generate human-like trajectories for both the CoM and the swing foot. The model's predictive accuracy is empirically validated against the kinematic behavior of 12 healthy subjects walking at three self-selected speeds. Furthermore, the proposed planner is mathematically compatible with an extended formulation of the Passive Motion Paradigm ($λ_0$-PMP), establishing a comprehensive theoretical foundation for decentralized, hierarchical architectures of semi-autonomous controllers in both human motor control and assistive robotics.
TOLEBI: Learning Fault-Tolerant Bipedal Locomotion via Online Status Estimation and Fallibility Rewards
Department of Intelligence and Information, Graduate School of Convergence Science and Technology, Seoul National University（智能信息系，融合科学与技术研究生院，首尔国立大学）；Artificial Intelligence Institute (AIIS), Seoul National University（人工智能研究院（AIIS），首尔国立大学）；Advanced Institutes of Convergence Technology (AICT), Suwon（融合技术高级研究院（AICT），Suwon）
Highly dynamic locomotion control of biped robot enhanced by swing arms
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences（中国科学院香港创新研究院）；University of Chinese Academy of Sciences（中国科学院大学）
Learning Terrain Aware Bipedal Locomotion via Reduced Dimensional Perceptual Representations
Electrical and Computer Engineering, The Ohio State University（电气与计算机工程系，俄亥俄州立大学）；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）
LIPM-Guided Reinforcement Learning for Stable and Perceptive Locomotion in Bipedal Robots
School of Automation and Intelligent Manufacturing (AIM), Southern University of Science and Technology（自动化与智能制造学院，南方科技大学）；Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology（土木与环境工程系，香港科技大学）；Department of Mechanical Engineering, The University of Hong Kong（机械工程系，香港大学）；Zhejiang University-University of Illinois Urbana-Champaign Institute (ZJUI), Zhejiang University（浙江大学-伊利诺伊大学厄巴纳-香槟分校联合研究所，浙江大学）；LimX Dynamics, Shenzhen, China（深圳LimX动力有限公司）
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）
Bipedal-Walking-Dynamics Model on Granular Terrains
Department of Mechanical and Aerospace Engineering, Rutgers University（罗格斯大学机械与航空航天工程系）；Bridgewater Raritan High School（布里奇沃特-拉里坦高中）；State Key Lab of Fluid Power Transmission and Control and the School of Mechanical Engineering, Zhejiang University（浙江大学流体动力传动与控制国家重点实验室和机械工程学院）
