Human Aware Robotics Modeling Human Motor Skills For The Design Planning And Control Of A New Generation Of Robotic Devices

This book moves from a thorough investigation of human capabilities during movements and interactions with objects and environment and translates those principles into the design planning and control of innovative mechatronic systems, providing significant advancements in the fields of human–robot interaction, autonomous robots, prosthetics and assistive devices. The work presented in this monograph is characterized by a significant paradigmatic shift with respect to typical approaches, as it always place the human at the center of the technology developed, and the human represents the starting point and the actual beneficiary of the developed solutions. The content of this book is targeted to robotics and neuroscience enthusiasts, researchers and makers, students and simple lovers of the matter.

Human Modelling for Bio-inspired Robotics: Mechanical Engineering in Assistive Technologies presents the most cutting-edge research outcomes in the area of mechanical and control aspects of human functions for macro-scale (human size) applications. Intended to provide researchers both in academia and industry with key content on which to base their developments, this book is organized and written by senior experts in their fields. Human Modeling for Bio-Inspired Robotics: Mechanical Engineering in Assistive Technologies offers a system-level investigation into human mechanisms that inspire the development of assistive technologies and humanoid robotics, including topics in modelling of anatomical, musculoskeletal, neural and cognitive systems, as well as motor skills, adaptation and integration. Each chapter is written by a subject expert and discusses its background, research challenges, key outcomes, application, and future trends. This book will be especially useful for academic and industry researchers in this exciting field, as well as graduate-level students to bring them up to speed with the latest technology in mechanical design and control aspects of the area. Previous knowledge of the fundamentals of kinematics, dynamics, control, and signal processing is assumed. Presents the most recent research outcomes in the area of mechanical and control aspects of human functions for macro-scale (human size) applications Covers background information and fundamental concepts of human modelling Includes modelling of anatomical, musculoskeletal, neural and cognitive systems, as well as motor skills, adaptation, integration, and safety issues Assumes previous knowledge of the fundamentals of kinematics, dynamics, control, and signal processing

The new frontiers of robotics research foresee future scenarios where artificial agents will leave the laboratory to progressively take part in the activities of our daily life. This will require robots to have very sophisticated perceptual and action skills in many intelligence-demanding applications, with particular reference to the ability to seamlessly interact with humans. It will be crucial for the next generation of robots to understand their human partners and at the same time to be intuitively understood by them. In this context, a deep understanding of human motion is essential for robotics applications, where the ability to detect, represent and recognize human dynamics and the capability for generating appropriate movements in response sets the scene for higher-level tasks. This book provides a comprehensive overview of this challenging research field, closing the loop between perception and action, and between human-studies and robotics. The book is organized in three main parts. The first part focuses on human motion perception, with contributions analyzing the neural substrates of human action understanding, how perception is influenced by motor control, and how it develops over time and is exploited in social contexts. The second part considers motion perception from the computational perspective, providing perspectives on cutting-edge solutions available from the Computer Vision and Machine Learning research fields, addressing higher-level perceptual tasks. Finally, the third part takes into account the implications for robotics, with chapters on how motor control is achieved in the latest generation of artificial agents and how such technologies have been exploited to favor human-robot interaction. This book considers the complete human-robot cycle, from an examination of how humans perceive motion and act in the world, to models for motion perception and control in artificial agents. In this respect, the book will provide insights into the perception and action loop in humans and machines, joining together aspects that are often addressed in independent investigations. As a consequence, this book positions itself in a field at the intersection of such different disciplines as Robotics, Neuroscience, Cognitive Science, Psychology, Computer Vision, and Machine Learning. By bridging these different research domains, the book offers a common reference point for researchers interested in human motion for different applications and from different standpoints, spanning Neuroscience, Human Motor Control, Robotics, Human-Robot Interaction, Computer Vision and Machine Learning. Chapter 'The Importance of the Affective Component of Movement in Action Understanding' of this book is available open access under a CC BY 4.0 license at link.springer.com.

Humans are endowed with extraordinary sensory-motor capabilities that enable a successful interaction with and exploration of the environment, as is the case of human manipulation. Understanding and modeling these capabilities represents an important topic not only for neuroscience but also for robotics in a mutual inspiration, both to inform the design and control of artificial systems and, at the same time, to increase knowledge on the biological side. Within this context, synergies -- i.e., goal-directed actions that constrain multi DOFs of the human body and can be defined at the kinematic, muscular, neural level -- have gained increasing attention as a general simplified approach to shape the development of simple and effective artificial devices. The execution of such purposeful sensory-motor primitives on the biological side leverages on the interplay of the sensory-motor control at central and peripheral level, and the interaction of the human body with the external world. This interaction is particularly important considering the new concept of robotic soft manipulation, i.e. soft, adaptable yet robust robotic hands that can deform with the external environment to multiply their grasping and manipulation capabilities. Under this regard, a preeminent role is reserved to touch, being that skin isour primary organ to shape our knowledge of the external world and, hence, to modify it, in interaction with the efferent parts. This Research Topic reports results on the mutual inspiration between neuroscience and robotics, and on how it is possible to translate neuroscientific findings on human manipulation into engineering guidelines for simplified systems able to take full advantage from the interaction and hence exploitation of environmental constraints for task accomplishment and knowledge acquisition.

In the last decades robots are expected to be of increasing intelligence to deal with a large range of tasks. Especially, robots are supposed to be able to learn manipulation skills from humans. To this end, a number of learning algorithms and techniques have been developed and successfully implemented for various robotic tasks. Among these methods, learning from demonstrations (LfD) enables robots to effectively and efficiently acquire skills by learning from human demonstrators, such that a robot can be quickly programmed to perform a new task. This book introduces recent results on the development of advanced LfD-based learning and control approaches to improve the robot dexterous manipulation. First, there's an introduction to the simulation tools and robot platforms used in the authors' research. In order to enable a robot learning of human-like adaptive skills, the book explains how to transfer a human user’s arm variable stiffness to the robot, based on the online estimation from the muscle electromyography (EMG). Next, the motion and impedance profiles can be both modelled by dynamical movement primitives such that both of them can be planned and generalized for new tasks. Furthermore, the book introduces how to learn the correlation between signals collected from demonstration, i.e., motion trajectory, stiffness profile estimated from EMG and interaction force, using statistical models such as hidden semi-Markov model and Gaussian Mixture Regression. Several widely used human-robot interaction interfaces (such as motion capture-based teleoperation) are presented, which allow a human user to interact with a robot and transfer movements to it in both simulation and real-word environments. Finally, improved performance of robot manipulation resulted from neural network enhanced control strategies is presented. A large number of examples of simulation and experiments of daily life tasks are included in this book to facilitate better understanding of the readers.

How do humans perceive communicative gesture behavior in robots? Although gesture is a crucial feature of social interaction, this research question is still largely unexplored in the field of social robotics. The present work thus sets out to investigate how robot gesture can be used to design and realize more natural and human-like communication capabilities for social robots. The adopted approach is twofold. Firstly, the technical challenges encountered when implementing a speech-gesture generation model on a robotic platform are addressed. The realized framework enables a humanoid robot to produce finely synchronized speech and co-verbal hand and arm gestures. In contrast to many existing systems, these gestures are not limited to a predefined repertoire of motor actions but are flexibly generated at run-time. Secondly, the achieved expressiveness is exploited in controlled experiments to gain a deeper understanding of how robot gesture might impact human experience and evaluation of human-robot interaction. The findings reveal that participants evaluate the robot more positively when non-verbal behaviors such as hand and arm gestures are displayed along with speech. Surprisingly, this effect was particularly pronounced when the robot's gesturing behavior was partly incongruent with speech. These findings contribute new insights into human perception of communicative robot gesture and ultimately support the presented approach of endowing social robots with such non-verbal behaviors.

This book provides readers with a solid set of diversified and essential tools for the theoretical modeling and control of complex robotic systems, as well as for digital human modeling and realistic motion generation. Following a comprehensive introduction to the fundamentals of robotic kinematics, dynamics and control systems design, the author extends robotic modeling procedures and motion algorithms to a much higher-dimensional, larger scale and more sophisticated research area, namely digital human modeling. Most of the methods are illustrated by MATLABTM codes and sample graphical visualizations, offering a unique closed loop between conceptual understanding and visualization. Readers are guided through practicing and creating 3D graphics for robot arms as well as digital human models in MATLABTM, and through driving them for real-time animation. This work is intended to serve as a robotics textbook with an extension to digital human modeling for senior undergraduate and graduate engineering students. At the same time, it represents a comprehensive reference guide for all researchers, scientists and professionals eager to learn the fundamentals of robotic systems as well as the basic methods of digital human modeling and motion generation.

Humanoid robotics have made remarkable progress since the dawn of robotics. So why don't we have humanoid robot assistants in day-to-day life yet? This book analyzes the keys to building a successful humanoid robot for field robotics, where collisions become an unavoidable part of the game. The author argues that the design goal should be real anthropomorphism, as opposed to mere human-like appearance. He deduces three major characteristics to aim for when designing a humanoid robot, particularly robot hands: - Robustness against impacts - Fast dynamics - Human-like grasping and manipulation performance Instead of blindly copying human anatomy, this book opts for a holistic design methodology. It analyzes human hands and existing robot hands to elucidate the important functionalities that are the building blocks toward these necessary characteristics. They are the keys to designing an anthropomorphic robot hand, as illustrated in the high performance anthropomorphic Awiwi Hand presented in this book. This is not only a handbook for robot hand designers. It gives a comprehensive survey and analysis of the state of the art in robot hands as well as the human anatomy. It is also aimed at researchers and roboticists interested in the underlying functionalities of hands, grasping and manipulation. The methodology of functional abstraction is not limited to robot hands, it can also help realize a new generation of humanoid robots to accommodate a broader spectrum of the needs of human society.

The concepts represented in this textbook are explored for the first time in assistive and rehabilitation robotics, which is the combination of physical, cognitive, and social human-robot interaction to empower gait rehabilitation and assist human mobility. The aim is to consolidate the methodologies, modules, and technologies implemented in lower-limb exoskeletons, smart walkers, and social robots when human gait assistance and rehabilitation are the primary targets. This book presents the combination of emergent technologies in healthcare applications and robotics science, such as soft robotics, force control, novel sensing methods, brain-computer interfaces, serious games, automatic learning, and motion planning. From the clinical perspective, case studies are presented for testing and evaluating how those robots interact with humans, analyzing acceptance, perception, biomechanics factors, and physiological mechanisms of recovery during the robotic assistance or therapy. Interfacing Humans and Robots for Gait Assistance and Rehabilitation will enable undergraduate and graduate students of biomedical engineering, rehabilitation engineering, robotics, and health sciences to understand the clinical needs, technology, and science of human-robot interaction behind robotic devices for rehabilitation, and the evidence and implications related to the implementation of those devices in actual therapy and daily life applications.

A synthesis of biomechanics and neural control that draws on recent advances in robotics to address control problems solved by the human sensorimotor system. This book proposes a transdisciplinary approach to investigating human motor control that synthesizes musculoskeletal biomechanics and neural control. The authors argue that this integrated approach—which uses the framework of robotics to understand sensorimotor control problems—offers a more complete and accurate description than either a purely neural computational approach or a purely biomechanical one. The authors offer an account of motor control in which explanatory models are based on experimental evidence using mathematical approaches reminiscent of physics. These computational models yield algorithms for motor control that may be used as tools to investigate or treat diseases of the sensorimotor system and to guide the development of algorithms and hardware that can be incorporated into products designed to assist with the tasks of daily living. The authors focus on the insights their approach offers in understanding how movement of the arm is controlled and how the control adapts to changing environments. The book begins with muscle mechanics and control, progresses in a logical manner to planning and behavior, and describes applications in neurorehabilitation and robotics. The material is self-contained, and accessible to researchers and professionals in a range of fields, including psychology, kinesiology, neurology, computer science, and robotics.