This paper presents a novel approach to solve simultaneously the problems of human activity recognition and whole-body motion and dynamics prediction for real-time applications. Starting from the dynamics of human motion and motor system theory, the notion of mixture of experts from deep learning has been extended to address this problem. In the proposed approach, experts are modelled as a sequence-to-sequence recurrent neural networks (RNN) architecture. Experiments show the results of 66-DoF real-world human motion prediction and action recognition during different tasks like walking and rotating. The code associated with this paper is available at: \url{github.com/ami-iit/paper_darvish_2022_humanoids_action-kindyn-predicition}
Model-agnostic Meta-learning for Adaptive Gait Phase and Terrain Geometry Estimation with Wearable Soft Sensors
School of Mechanical Engineering, Purdue University（机械工程学院，普渡大学）；Dept. of Mechanical Engineering & Materials Science, Yale University（机械工程与材料科学系，耶鲁大学）；Dept. of Mechanical Engineering, University of Maryland Baltimore County（机械工程系，马里兰大学巴尔的摩县分校）
MateRobot: Material Recognition in Wearable Robotics for People with Visual Impairments
Institute for Robotics and Anthropomatics, Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院机器人与人体工程学研究所）；University of Oxford（牛津大学）；Hangzhou SurImage Technology Company Ltd.（杭州 SurImage 科技有限公司）
Perception Framework through Real-Time Semantic Segmentation and Scene Recognition on a Wearable System for the Visually Impaired
Institute for Anthropomatics and Robotics, Karlsruhe Institute of Technology（卡尔斯鲁厄理工学院人形机器人与智能系统研究所）；Hangzhou SurImage Technology Company Ltd.（杭州 SurImage 科技有限公司）；Hangzhou KrVision Technology Company Ltd.（杭州 KrVision 科技有限公司）
Towards a General Humanoid Loco-Manipulation Model via Egocentric Whole-Body Human Data Pretraining
Alibaba Group（阿里巴巴集团）；Sichuan University（四川大学）；Shanghai Innovation Institute（上海创新研究院）；Beihang University（北京航空航天大学）；Hong Kong University of Science and Technology（香港科技大学）
Simultaneous Contact Sequence and Patch Planning for Dynamic Locomotion
Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich (TUM), Germany（慕尼黑机器人与机器智能研究所（MIRMI）、慕尼黑技术大学（TUM））；Tandon School of Engineering, New York University (NYU), USA（纽约大学Tandon工程学院）
A Human Motion Compensation Framework for a Supernumerary Robotic Arm
Shenyang Institute of Automation, Chinese Academy of Sciences（中国科学院沈阳自动化研究所）；Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences（中国科学院机器人与智能制造创新研究院）；Istituto Italiano di Tecnologia（意大利理工学院）
RoboDuet: Learning a Cooperative Policy for Whole-body Legged Loco-Manipulation
Tsinghua University（清华大学）；University of San Diego（圣地亚哥大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Institute for Interdisciplinary Information Sciences, Tsinghua University（清华大学交叉信息研究院）；Shanghai Qi Zhi Institute（上海期智研究院）；Tsinghua Shenzhen International Graduate School（清华大学深圳国际研究生院）；Jianghuai Advance Technology Center（江淮先进技术中心）
Intelligent upper-limb exoskeleton integrated with soft wearable bioelectronics and deep-learning for human intention-driven strength augmentation based on sensory feedback
Dongguk University（东国大学）；Georgia Institute of Technology（佐治亚理工学院）；Yonsei University（延世大学）；Emory University School of Medicine（埃默里大学医学院）
Scalable Trajectory Generation for Whole-Body Mobile Manipulation
Institute for AI, Peking University（人工智能研究院，北京大学）；Institute of Unmanned System, Beihang University（无人系统研究院，北航）；School of Psychological and Cognitive Sciences, Peking University（心理学与认知科学学院，北京大学）；State Key Laboratory of General Artificial Intelligence（通用人工智能国家重点实验室）；Beijing Key Laboratory of Behavior and Mental Health, Peking University（北京行为与心理健康重点实验室，北京大学）；Yuanpei College, Peking University（元培学院，北京大学）；Embodied Intelligence Lab, PKU-Wuhan Institute for Artificial Intelligence（具身智能实验室，PKU-武汉人工智能研究所）
