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Proceedings ArticleDOI

An open-source simulator for cognitive robotics research: the prototype of the iCub humanoid robot simulator

TL;DR: The prototype of a new computer simulator for the humanoid robot iCub, developed as part of a joint effort with the European project "ITALK" on the integration and transfer of action and language knowledge in cognitive robots.
Abstract: This paper presents the prototype of a new computer simulator for the humanoid robot iCub. The iCub is a new open-source humanoid robot developed as a result of the "RobotCub" project, a collaborative European project aiming at developing a new open-source cognitive robotics platform. The iCub simulator has been developed as part of a joint effort with the European project "ITALK" on the integration and transfer of action and language knowledge in cognitive robots. This is available open-source to all researchers interested in cognitive robotics experiments with the iCub humanoid platform.

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BookDOI
29 Mar 2013
TL;DR: This book introduces the concept of intrinsic motivation in artificial systems, reviews the relevant literature, offers insights from the neural and behavioural sciences, and presents novel tools for research.
Abstract: It has become clear to researchers in robotics and adaptive behaviour that current approaches are yielding systems with limited autonomy and capacity for self-improvement. To learn autonomously and in a cumulative fashion is one of the hallmarks of intelligence, and we know that higher mammals engage in exploratory activities that are not directed to pursue goals of immediate relevance for survival and reproduction but are instead driven by intrinsic motivations such as curiosity, interest in novel stimuli or surprising events, and interest in learning new behaviours. The adaptive value of such intrinsically motivated activities lies in the fact that they allow the cumulative acquisition of knowledge and skills that can be used later to accomplish tness-enhancing goals. Intrinsic motivations continue during adulthood, and in humans they underlie lifelong learning, artistic creativity, and scientific discovery, while they are also the basis for processes that strongly affect human well-being, such as the sense of competence, self-determination, and self-esteem. This book has two aims: to present the state of the art in research on intrinsically motivated learning, and to identify the related scientific and technological open challenges and most promising research directions. The book introduces the concept of intrinsic motivation in artificial systems, reviews the relevant literature, offers insights from the neural and behavioural sciences, and presents novel tools for research. The book is organized into six parts: the chapters in Part I give general overviews on the concept of intrinsic motivations, their function, and possible mechanisms for implementing them; Parts II, III, and IV focus on three classes of intrinsic motivation mechanisms, those based on predictors, on novelty, and on competence; Part V discusses mechanisms that are complementary to intrinsic motivations; and Part VI introduces tools and experimental frameworks for investigating intrinsic motivations.The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots. The contributing authors are among the pioneers carrying out fundamental work on this topic, drawn from related disciplines such as artificial intelligence, robotics, artificial life, evolution, machine learning, developmental psychology, cognitive science, and neuroscience. The book will be of value to graduate students and academic researchers in these domains, and to engineers engaged with the design of autonomous, adaptive robots.

253 citations

Journal ArticleDOI
TL;DR: This work proposes a new methodology to find a feasible catching configuration in a probabilistic manner and uses the dynamical systems approach to encode motion from several demonstrations, which enables a rapid and reactive adaptation of the arm motion in the presence of sensor uncertainty.
Abstract: We address the difficult problem of catching in-flight objects with uneven shapes This requires the solution of three complex problems: accurate prediction of the trajectory of fastmoving objects, predicting the feasible catching configuration, and planning the arm motion, and all within milliseconds We follow a programming-by-demonstration approach in order to learn, from throwing examples, models of the object dynamics and arm movement We propose a new methodology to find a feasible catching configuration in a probabilistic manner We use the dynamical systems approach to encode motion from several demonstrations This enables a rapid and reactive adaptation of the arm motion in the presence of sensor uncertainty We validate the approach in simulation with the iCub humanoid robot and in real-world experiments with the KUKA LWR 4+ (7-degree-of-freedom arm robot) to catch a hammer, a tennis racket, an empty bottle, a partially filled bottle, and a cardboard box

186 citations

Journal ArticleDOI
TL;DR: Six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment.
Abstract: Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamoring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensorimotor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialog between two fictional characters: Ernest, the “experimenter,” and Mary, the “computational modeler.” The dialog consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modeling.

176 citations


Cites background or methods from "An open-source simulator for cognit..."

  • ...Macura et al.’s (2009) model also implements the stimulus compatibility effects demonstrated by Tucker and Ellis (2001) in a simulation model of iCub (Tikhanoff et al., 2008)....

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  • ...For example, a simulator for the iCub robot (Metta et al., 2008; Tikhanoff et al., 2008) magnifies the value a research group can extract from the physical robot by making it more practical to share a single robot between several researchers....

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  • ...These include realistic models of an existing robot, such as simulation models of the iCub humanoid platform (Tikhanoff et al., 2008), which is an open source robotic platform specifically developed for cognitive research, and of mobile robots such as khepera (Nolfi and Floreano, 2000)....

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Journal ArticleDOI
TL;DR: This work will focus on the modeling of the evolutionary and developmental acquisition of linguistic capabilities based on the principles of symbol grounding, and discusses the benefits of the use of humanoid robotic platform, and specifically of the open source iCub platform, for the study of embodied cognition.

111 citations

Journal ArticleDOI
TL;DR: This paper reviews several widely used perception methods of HRI in social robots and investigates general perception tasks crucial for HRI, such as where the objects are located in the rooms, what objects are in the scene, and how they interact with humans.
Abstract: For human–robot interaction (HRI), perception is one of the most important capabilities. This paper reviews several widely used perception methods of HRI in social robots. Specifically, we investigate general perception tasks crucial for HRI, such as where the objects are located in the rooms, what objects are in the scene, and how they interact with humans. We first enumerate representative social robots and summarize the most three important perception methods from these robots: feature extraction, dimensionality reduction, and semantic understanding. For feature extraction, four widely used signals including visual-based, audio-based, tactile-based and rang sensors-based are reviewed, and they are compared based on their advantages and disadvantages. For dimensionality reduction, representative methods including principle component analysis (PCA), linear discriminant analysis (LDA), and locality preserving projections (LPP) are reviewed. For semantic understanding, conventional techniques for several typical applications such as object recognition, object tracking, object segmentation, and speaker localization are discussed, and their characteristics and limitations are also analyzed. Moreover, several popular data sets used in social robotics and published semantic understanding results are analyzed and compared in light of our analysis of HRI perception methods. Lastly, we suggest important future work to analyze fundamental questions on perception methods in HRI.

103 citations

References
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Proceedings ArticleDOI
01 Sep 2004
TL;DR: Gazebo is designed to fill this niche by creating a 3D dynamic multi-robot environment capable of recreating the complex worlds that would be encountered by the next generation of mobile robots.
Abstract: Simulators have played a critical role in robotics research as tools for quick and efficient testing of new concepts, strategies, and algorithms. To date, most simulators have been restricted to 2D worlds, and few have matured to the point where they are both highly capable and easily adaptable. Gazebo is designed to fill this niche by creating a 3D dynamic multi-robot environment capable of recreating the complex worlds that would be encountered by the next generation of mobile robots. Its open source status, fine grained control, and high fidelity place Gazebo in a unique position to become more than just a stepping stone between the drawing board and real hardware: data visualization, simulation of remote environments, and even reverse engineering of blackbox systems are all possible applications. Gazebo is developed in cooperation with the Player and Stage projects (Gerkey, B. P., et al., July 2003), (Gerkey, B. P., et al., May 2001), (Vaughan, R. T., et al., Oct. 2003), and is available from http://playerstage.sourceforge.net/gazebo/ gazebo.html.

2,824 citations

Proceedings Article
01 Jul 2003
TL;DR: Current usage of Player and Stage is reviewed, and some interesting research opportunities opened up by this infrastructure are identified.
Abstract: This paper describes the Player/Stage software tools applied to multi-robot, distributed-robot and sensor network systems. Player is a robot device server that provides network transparent robot control. Player seeks to constrain controller design as little as possible; it is device independent, non-locking and language- and style-neutral. Stage is a lightweight, highly configurable robot simulator that supports large populations. Player/Stage is a community Free Software project. Current usage of Player and Stage is reviewed, and some interesting research opportunities opened up by this infrastructure are identified.

1,628 citations

MonographDOI
01 Mar 2004
TL;DR: This book describes the basic concepts and methodologies of evolutionary robotics and the results achieved so far, and describes the clear presentation of a set of empirical experiments of increasing complexity.
Abstract: Evolutionary robotics is a new technique for the automatic creation of autonomous robots. Inspired by the Darwinian principle of selective reproduction of the fittest, it views robots as autonomous artificial organisms that develop their own skills in close interaction with the environment and without human intervention. Drawing heavily on biology and ethology, it uses the tools of neural networks, genetic algorithms, dynamic systems, and biomorphic engineering. The resulting robots share with simple biological systems the characteristics of robustness, simplicity, small size, flexibility, and modularity. In evolutionary robotics, an initial population of artificial chromosomes, each encoding the control system of a robot, is randomly created and put into the environment. Each robot is then free to act (move, look around, manipulate) according to its genetically specified controller while its performance on various tasks is automatically evaluated. The fittest robots then "reproduce" by swapping parts of their genetic material with small random mutations. The process is repeated until the "birth" of a robot that satisfies the performance criteria. This book describes the basic concepts and methodologies of evolutionary robotics and the results achieved so far. An important feature is the clear presentation of a set of empirical experiments of increasing complexity. Software with a graphic interface, freely available on a Web page, will allow the reader to replicate and vary (in simulation and on real robots) most of the experiments.

1,084 citations

Journal ArticleDOI
TL;DR: Webots™ lets you define and modify a complete mobile robotics setup, even several different robots sharing the same environment, and enable you to transfer your control programs to several commercially available real mobile robots.
Abstract: Cyberbotics Ltd. develops Webots™, a mobile robotics simulation software that provides you with a rapid prototyping environment for modelling, programming and simulating mobile robots. The provided robot libraries enable you to transfer your control programs to several commercially available real mobile robots. Webots™ lets you define and modify a complete mobile robotics setup, even several different robots sharing the same environment. For each object, you can define a number of properties, such as shape, color, texture, mass, friction, etc. You can equip each robot with a large number of available sensors and actuators. You can program these robots using your favorite development environment, simulate them and optionally transfer the resulting programs onto your real robots. Webots™ has been developed in collaboration with the Swiss Federal Institute of Technology in Lausanne, thoroughly tested, well documented and continuously maintained for over 7 years. It is now the main commercial product availabl...

1,062 citations


"An open-source simulator for cognit..." refers methods in this paper

  • ...The very first iCub simulator prototype was developed using the commercial Webots package [9,16], a professional robotic simulator which is widely used in academia and research....

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Journal ArticleDOI
TL;DR: The goal of YARP is to minimize the effort devoted to infrastructure-level software development by facilitating code reuse, modularity and so maximize research-level development and collaboration by encapsulating lessons from the experience in building humanoid robots.
Abstract: We describe YARP, Yet Another Robot Platform, an open-source project that encapsulates lessons from our experience in building humanoid robots. The goal of YARP is to minimize the effort devoted to infrastructure-level software development by facilitating code reuse, modularity and so maximize research-level development and collaboration. Humanoid robotics is a "bleeding edge" field of research, with constant flux in sensors, actuators, and processors. Code reuse and maintenance is therefore a significant challenge. We describe the main problems we faced and the solutions we adopted. In short, the main features of YARP include support for inter-process communication, image processing as well as a class hierarchy to ease code reuse across different hardware platforms. YARP is currently used and tested on Windows, Linux and QNX6 which are common operating systems used in robotics.

640 citations