In the last two decades the scientific community has shown a great interest in understanding and shaping the interaction mechanisms between humans and robots. The interaction implies communication between two dyadic agents and, if the type of interaction is physical, the communication is represented by the set of forces exchanged during the interaction. Within this context, the role of quantifying these forces becomes of pivotal importance for understanding the interaction mechanisms. At the current scientific stage, classical robots are built to act for humans, but the scientific demand is going towards the direction of robots that will have to collaborate with humans. This will be possible by providing the robots with sufficient pieces of information of the agent they are interacting with (i.e., kinematic and dynamic model of the human). In a modern age where humans need the help of robots, apparently in an opposite trend, this thesis attempts to answer the following questions: Do robots need humans? Should robots know their human partners? A tentative answer is provided here in the form of a novel framework for the simultaneous human whole-body motion tracking and dynamics estimation, in a real-time scenario. The framework encompasses a set of body-mounted sensors and a probabilistic algorithm able of estimating physical quantities that in humans are not directly measurable (i.e., torques and internal forces). This thesis is mainly focussed on the paramount role in retrieving the human dynamics estimation but straightforwardly it leaves the door open to the next development step: passing the human dynamics feedback to the robot controllers. This step will enable the robot with the capability to observe and understand the human partner by generating an enhanced (intentional) interaction.
Whole-Body Control for Velocity-Controlled Mobile Collaborative Robots Using Coupling Dynamic Movement Primitives
Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS)（深圳人工智能与机器人研究院（AIRS））；Harbin Institute of Technology（哈尔滨工业大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））
Enhancing Robot Explanation Capabilities through Vision-Language Models: a Preliminary Study by Interpreting Visual Inputs for Improved Human-Robot Interaction
DTRT: Enhancing Human Intent Estimation and Role Allocation for Physical Human-Robot Collaboration
CAS Engineering Laboratory for Intelligent Industrial Vision, Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所CAS工程视觉实验室）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）
Enhancing Speech Instruction Understanding and Disambiguation in Robotics via Speech Prosody
IT University of Copenhagen（丹麦技术大学）；University of Florida（佛罗里达大学）；Brown University（布朗大学）；Intelligent Agents Research Group（智能代理研究组）；Intelligent Robot Lab（智能机器人实验室）
Enhancing the NAO: Extending Capabilities of Legacy Robots for Long-Term Research
SaPHaRI Lab, Human Fusions Institute（SaPHaRI实验室，人类融合研究所）；Department of Electrical, Computer, and Systems Engineering（电气、计算机与系统工程系）；Department of Psychological Sciences/Department of Cognitive Science（心理学系/认知科学系）
BiConMP: A Nonlinear Model Predictive Control Framework for Whole Body Motion Planning
Tandon School of Engineering, New York University（纽约大学坦登工程学院）；Max-Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；Oxford Robotics Institute, University of Oxford（牛津大学牛津机器人研究所）
A Whole-Body Disturbance Rejection Control Framework for Dynamic Motions in Legged Robots
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology（人工智能与自动化学院，华中科技大学）；Huazhong University of Science and Technology（华中科技大学）；State Key Laboratory of Intelligent Manufacturing Equipment and Technology, Huazhong University of Science and Technology（智能制造装备及技术国家重点实验室，华中科技大学）
A Whole-Body Motion Imitation Framework from Human Data for Full-Size Humanoid Robot
The State Key Laboratory of Industrial Control and Technology of Zhejiang University（浙江大学工业控制技术状态重点实验室）；Zhejiang Humanoid Robot Innovation Center（浙江人形机器人创新中心）；Department of Engineering Mechanics of Zhejiang University（浙江大学工程力学系）
Whole-body Multi-contact Motion Control for Humanoid Robots Based on Distributed Tactile Sensors
CNRS-AIST JRL (Joint Robotics Laboratory), IRL and National Institute of Advanced Industrial Science and Technology (AIST)（CNRS-AIST联合机器人实验室、IRL和国家先进工业科学与技术研究所）
Integrable Whole-body Orientation Coordinates for Legged Robots
University of Pennsylvania（宾夕法尼亚大学）；Boardwalk Robotics（博德沃克机器人公司）；Boston Dynamics Artificial Intelligence Institute（波士顿动力人工智能研究所）；Florida Institute for Human and Machine Cognition（佛罗里达人机认知研究所）
Whole-Body Control With Terrain Estimation of A 6-DoF Wheeled Bipedal Robot
School of Intelligent Systems Engineering, Sun Yat-sen University（中山大学智能系统工程学院）；Direct Drive Technology Limited（直接驱动技术有限公司）；Suzhou Nuclear Power Research Institute Co., Ltd（苏州核电研究所有限公司）
