Human Motion Generation: A Survey

Zhu, Wentao; Ma, Xiaoxuan; Ro, Dongwoo; Ci, Hai; Zhang, Jinlu; Shi, Jiaxin; Gao, Feng; Tian, Qi; Wang, Yizhou

doi:10.1109/tpami.2023.3330935

Cited by 17 publications

References 176 publications

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Conditional Adversarial Motion Priors by a Novel Retargeting Method for Versatile Humanoid Robot Control

Zhang,

Li,

et al. 2024

Adaptive Control & Signal

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Significant advancements have been made in the field of humanoid robot, particularly in walking control strategies. However, achieving straight‐legged walking remains a challenge. Both the traditional model‐based and the learning‐based control methods confront with difficulties in achieving natural humanoid gait feature. To address this issue, a general motion retargeting method is developed and also evaluated for humanoid robots with different structure, size and degrees of freedom. Moreover, a conditional adversarial motion priors method is proposed based on reinforcement learning and validated on the humanoid robot GTX‐III. Through various motion segments from the motion capture database, it is shown that this method can successfully enable the humanoid robot to perform straight‐legged walking with flexible and natural transitions between different gaits within a single discriminator network.

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Conditional Adversarial Motion Priors by a Novel Retargeting Method for Versatile Humanoid Robot Control

Zhang,

Li,

et al. 2024

Adaptive Control & Signal

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Monomer Trapping Synthesis Toward Dynamic Nanoconfinement Self‐healing Eutectogels for Strain Sensing

Lv,

Li,

Yang

et al. 2024

Advanced Science

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The rapid advancement in attractive platforms such as biomedicine and human‐machine interaction has generated urgent demands for intelligent materials with high strength, flexibility, and self‐healing capabilities. However, existing self‐healing ability materials are challenged by a trade‐off between high strength, low elastic modulus, and healing ability due to the inherent low strength of noncovalent bonding. Here, drawing inspiration from human fibroblasts, a monomer trapping synthesis strategy is presented based on the dissociation and reconfiguration in amphiphilic ionic restrictors (7000‐times volume monomer trapping) to develop a eutectogel. Benefiting from the nanoconfinement and dynamic interfacial interactions, the molecular chain backbone of the formed confined domains is mechanically reinforced while preserving soft movement capabilities. The resulting eutectogels demonstrate superior mechanical properties (1799% and 2753% higher tensile strength and toughness than pure polymerized deep eutectic solvent), excellent self‐healing efficiency (>90%), low tangential modulus (0.367 MPa during the working stage), and the ability to sensitively monitor human activities. This strategy is poised to offer a new perspective for developing high strength, low modulus, and self‐healing wearable electronics tailored to human body motion.

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