Imitation And Social Learning In Robots Humans And Animals

Mechanisms of imitation and social matching play a fundamental role in development, communication, interaction, learning and culture. Their investigation in different agents (animals, humans and robots) has significantly influenced our understanding of the nature and origins of social intelligence. Whilst such issues have traditionally been studied in areas such as psychology, biology and ethnology, it has become increasingly recognised that a 'constructive approach' towards imitation and social learning via the synthesis of artificial agents can provide important insights into mechanisms and create artefacts that can be instructed and taught by imitation, demonstration, and social interaction rather than by explicit programming. This book studies increasingly sophisticated models and mechanisms of social matching behaviour and marks an important step towards the development of an interdisciplinary research field, consolidating and providing a valuable reference for the increasing number of researchers in the field of imitation and social learning in robots, humans and animals.

An interdisciplinary overview of current research on imitation in animals and artifacts.

From an engineering standpoint, the increasing complexity of robotic systems and the increasing demand for more autonomously learning robots, has become essential. This book is largely based on the successful workshop “From motor to interaction learning in robots” held at the IEEE/RSJ International Conference on Intelligent Robot Systems. The major aim of the book is to give students interested the topics described above a chance to get started faster and researchers a helpful compandium.

This book makes a consolidated guided tour to the world of sociorobots (social or socialized robots). Sociorobots and assistive robots provide entertainment, assistance to the handicapped, companionship to the elderly and health care to autistic children and people with dementia. The book provides, in a fluent educational way, all major concepts, architectures and design methodologies. All types of sociorobots are examined, namely walking anthropomorphic, wheeled anthropomorphic, fixed-place anthropomorphic and zoomorphic sociorobots. The book provides an outline of sociorobot intelligent control architectures, robot learning and human robot interaction.

This book constitutes the refereed proceedings of the Third Workshop on Human Behavior Understanding, HBU 2012, held in Vilamoura, Portugal, in October 2012. The 14 revised papers presented were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on sensing human behavior; social and affective signals; human-robot interaction; imitation and learning from demonstration.

Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.

In this book the variety of humanoid robotic research can be obtained. This book is divided in four parts: Hardware Development: Components and Systems, Biped Motion: Walking, Running and Self-orientation, Sensing the Environment: Acquisition, Data Processing and Control and Mind Organisation: Learning and Interaction. The first part of the book deals with remarkable hardware developments, whereby complete humanoid robotic systems are as well described as partial solutions. In the second part diverse results around the biped motion of humanoid robots are presented. The autonomous, efficient and adaptive two-legged walking is one of the main challenge in humanoid robotics. The two-legged walking will enable humanoid robots to enter our environment without rearrangement. Developments in the field of visual sensors, data acquisition, processing and control are to be observed in third part of the book. In the fourth part some "mind building" and communication technologies are presented.

This unique text/reference provides a coherent and comprehensive overview of all aspects of video analysis of humans. Broad in coverage and accessible in style, the text presents original perspectives collected from preeminent researchers gathered from across the world. In addition to presenting state-of-the-art research, the book reviews the historical origins of the different existing methods, and predicts future trends and challenges. Features: with a Foreword by Professor Larry Davis; contains contributions from an international selection of leading authorities in the field; includes an extensive glossary; discusses the problems associated with detecting and tracking people through camera networks; examines topics related to determining the time-varying 3D pose of a person from video; investigates the representation and recognition of human and vehicular actions; reviews the most important applications of activity recognition, from biometrics and surveillance, to sports and driver assistance.