Fundamentals Of Robotics: Linking Perception To Action

Fundamentals Of Robotics: Linking Perception To Action

Author: Ming Xie

Publisher: World Scientific Publishing Company

Published: 2003-04-11

Total Pages: 718

ISBN-13: 9813102349

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Tomorrow's robots, which includes the humanoid robot, can perform task like tutoring children, working as tour guides, driving humans to and from work, do the family shopping etc. Tomorrow's robots will enhance lives in ways we never dreamed possible. No time to attend the decisive meeting on Asian strategy? Let your robot go for you and make the decisions. Not feeling well enough to go to the clinic? Let Dr Robot come to you, make a diagnosis, and get you the necessary medicine for treatment. No time to coach the soccer team this week? Let the robot do it for you.Tomorrow's robots will be the most exciting and revolutionary things to happen to the world since the invention of the automobile. It will change the way we work, play, think, and live. Because of this, nowadays robotics is one of the most dynamic fields of scientific research. These days, robotics is offered in almost every university in the world. Most mechanical engineering departments offer a similar course at both the undergraduate and graduate levels. And increasingly, many computer and electrical engineering departments are also offering it.This book will guide you, the curious beginner, from yesterday to tomorrow. The book will cover practical knowledge in understanding, developing, and using robots as versatile equipment to automate a variety of industrial processes or tasks. But, the book will also discuss the possibilities we can look forward to when we are capable of creating a vision-guided, learning machine.


Modelling Human Motion

Modelling Human Motion

Author: Nicoletta Noceti

Publisher: Springer Nature

Published: 2020-07-09

Total Pages: 351

ISBN-13: 3030467325

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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.


Deep Learning for Robot Perception and Cognition

Deep Learning for Robot Perception and Cognition

Author: Alexandros Iosifidis

Publisher: Academic Press

Published: 2022-02-04

Total Pages: 638

ISBN-13: 0323885721

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Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis


From Motor Learning to Interaction Learning in Robots

From Motor Learning to Interaction Learning in Robots

Author: Olivier Sigaud

Publisher: Springer Science & Business Media

Published: 2010-02-04

Total Pages: 534

ISBN-13: 3642051804

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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.


A Roadmap for Cognitive Development in Humanoid Robots

A Roadmap for Cognitive Development in Humanoid Robots

Author: David Vernon

Publisher: Springer Science & Business Media

Published: 2011-12-28

Total Pages: 233

ISBN-13: 364216904X

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This book addresses the central role played by development in cognition. The focus is on applying our knowledge of development in natural cognitive systems, specifically human infants, to the problem of creating artificial cognitive systems in the guise of humanoid robots. The approach is founded on the three-fold premise that (a) cognition is the process by which an autonomous self-governing agent acts effectively in the world in which it is embedded, (b) the dual purpose of cognition is to increase the agent's repertoire of effective actions and its power to anticipate the need for future actions and their outcomes, and (c) development plays an essential role in the realization of these cognitive capabilities. Our goal in this book is to identify the key design principles for cognitive development. We do this by bringing together insights from four areas: enactive cognitive science, developmental psychology, neurophysiology, and computational modelling. This results in roadmap comprising a set of forty-three guidelines for the design of a cognitive architecture and its deployment in a humanoid robot. The book includes a case study based on the iCub, an open-systems humanoid robot which has been designed specifically as a common platform for research on embodied cognitive systems .


The Developmental Organization of Robot Behavior

The Developmental Organization of Robot Behavior

Author: Roderic A. Grupen

Publisher: MIT Press

Published: 2023-03-14

Total Pages: 403

ISBN-13: 0262073005

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A comprehensive introduction to the mathematical foundations of movement and actuation that apply equally to animals and machines. This textbook offers a computational framework for the sensorimotor stage of development as applied to robotics. Much work in developmental robotics is based on ad hoc examples, without a full computational basis. This book's comprehensive and complete treatment fills the gap, drawing on the principal mechanisms of development in the first year of life to introduce what is essentially an operating system for developing robots. The goal is to apply principles of development to robot systems that not only achieve new levels of performance but also provide evidence for scientific theories of human development.


Action and Language Integration in Cognitive Systems

Action and Language Integration in Cognitive Systems

Author: Angelo Cangelosi

Publisher: Frontiers Media SA

Published: 2012-07-12

Total Pages: 113

ISBN-13: 2889190382

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Recent theoretical and experimental research on action and language processing in humans and animals clearly demonstrates the strict interaction and co-dependence between language and action. This has been demonstrated in neuroscientific investigations (e.g. Cappa&Perani, 2003; Pulvermuller 2003; Rizzolatti&Arbib, 1998), psychology experiments (e.g. Glenberg&Kaschak, 2002; Pecher&Zwaan 2005), evolutionary psychology (e.g. Corballis 2002) and computational modelling (e.g. Cangelosi&Parisi 2004; Massera et al. 2008). All these studies have important implication both for the understanding of the action basis of cognition in natural and artificial cognitive systems, as well as for the design of cognitive and communicative capabilities in robots (Cangelosi et al. 2005). The journal “Frontiers in Neurorobotics” is seeking submissions of new articles in the topic of action and language integration both in natural cognitive systems (e.g. humans and animals) and in artificial cognitive agents (robots and simulated agents). Manuscripts can regard new theoretical and computational investigations, as well as new neuroscientific and psychological investigations. Review articles in this topic are also welcome.


Approaches to Probabilistic Model Learning for Mobile Manipulation Robots

Approaches to Probabilistic Model Learning for Mobile Manipulation Robots

Author: Jürgen Sturm

Publisher: Springer

Published: 2013-12-12

Total Pages: 216

ISBN-13: 3642371604

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This book presents techniques that enable mobile manipulation robots to autonomously adapt to new situations. Covers kinematic modeling and learning; self-calibration; tactile sensing and object recognition; imitation learning and programming by demonstration.


New Frontiers in Human-robot Interaction

New Frontiers in Human-robot Interaction

Author: Kerstin Dautenhahn

Publisher: John Benjamins Publishing

Published: 2011

Total Pages: 339

ISBN-13: 9027204551

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Human–Robot Interaction (HRI) considers how people can interact with robots in order to enable robots to best interact with people. HRI presents many challenges with solutions requiring a unique combination of skills from many fields, including computer science, artificial intelligence, social sciences, ethology and engineering. We have specifically aimed this work to appeal to such a multi-disciplinary audience. This volume presents new and exciting material from HRI researchers who discuss research at the frontiers of HRI. The chapters address the human aspects of interaction, such as how a robot may understand, provide feedback and act as a social being in interaction with a human, to experimental studies and field implementations of human–robot collaboration ranging from joint action, robots practically and safely helping people in real world situations, robots helping people via rehabilitation and robots acquiring concepts from communication. This volume reflects current trends in this exciting research field.


Visual Perception for Humanoid Robots

Visual Perception for Humanoid Robots

Author: David Israel González Aguirre

Publisher: Springer

Published: 2018-09-01

Total Pages: 253

ISBN-13: 3319978411

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This book provides an overview of model-based environmental visual perception for humanoid robots. The visual perception of a humanoid robot creates a bidirectional bridge connecting sensor signals with internal representations of environmental objects. The objective of such perception systems is to answer two fundamental questions: What & where is it? To answer these questions using a sensor-to-representation bridge, coordinated processes are conducted to extract and exploit cues matching robot’s mental representations to physical entities. These include sensor & actuator modeling, calibration, filtering, and feature extraction for state estimation. This book discusses the following topics in depth: • Active Sensing: Robust probabilistic methods for optimal, high dynamic range image acquisition are suitable for use with inexpensive cameras. This enables ideal sensing in arbitrary environmental conditions encountered in human-centric spaces. The book quantitatively shows the importance of equipping robots with dependable visual sensing. • Feature Extraction & Recognition: Parameter-free, edge extraction methods based on structural graphs enable the representation of geometric primitives effectively and efficiently. This is done by eccentricity segmentation providing excellent recognition even on noisy & low-resolution images. Stereoscopic vision, Euclidean metric and graph-shape descriptors are shown to be powerful mechanisms for difficult recognition tasks. • Global Self-Localization & Depth Uncertainty Learning: Simultaneous feature matching for global localization and 6D self-pose estimation are addressed by a novel geometric and probabilistic concept using intersection of Gaussian spheres. The path from intuition to the closed-form optimal solution determining the robot location is described, including a supervised learning method for uncertainty depth modeling based on extensive ground-truth training data from a motion capture system. The methods and experiments are presented in self-contained chapters with comparisons and the state of the art. The algorithms were implemented and empirically evaluated on two humanoid robots: ARMAR III-A & B. The excellent robustness, performance and derived results received an award at the IEEE conference on humanoid robots and the contributions have been utilized for numerous visual manipulation tasks with demonstration at distinguished venues such as ICRA, CeBIT, IAS, and Automatica.