What Do We Learn About Development from Baby Robots?1
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Developmental Reasoning and Planning with Robot Through Enactive Interaction with Human Maxime Petit
Developmental reasoning and planning with robot through enactive interaction with human Maxime Petit To cite this version: Maxime Petit. Developmental reasoning and planning with robot through enactive interaction with human. Automatic. Université Claude Bernard - Lyon I, 2014. English. NNT : 2014LYO10037. tel-01015288 HAL Id: tel-01015288 https://tel.archives-ouvertes.fr/tel-01015288 Submitted on 26 Jun 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. N˚d’ordre 37 - 2014 Année 2013 THESE DE L’UNIVERSITE DE LYON présentée devant L’UNIVERSITE CLAUDE BERNARD LYON 1 Ecole Doctorale Neurosciences et Cognition pour l’obtention du Diplôme de Thèse (arrété du 7 août 2006) Discipline : SCIENCES COGNITIVES Option : INFORMATIQUE présentée et soutenue publiquement le 6 Mars 2014 par Maxime Raisonnement et Planification Développementale d’un Robot via une Interaction Enactive avec un Humain Developmental Reasoning and Planning with Robot through Enactive Interaction with Human dirigée par Peter F. Dominey devant le jury composé de : Pr. Rémi Gervais Président du jury Pr. Giorgio Metta Rapporteur Pr. Philippe Gaussier Rapporteur Pr. Chrystopher Nehaniv Examinateur Dr. Jean-Christophe Baillie Examinateur Dr. Peter Ford Dominey Directeur de thèse 2 Stem-Cell and Brain Research Insti- École doctorale Neurosciences et Cog- tute, INSERM U846 nition (ED 476 - NSCo) 18, avenue Doyen Lepine UCBL - Lyon 1 - Campus de Gerland 6975 Bron Cedex 50, avenue Tony Garnier 69366 Lyon Cedex 07 Pour mon père. -
New Technologies for Human Robot Interaction and Neuroprosthetics
University of Plymouth PEARL https://pearl.plymouth.ac.uk Faculty of Science and Engineering School of Engineering, Computing and Mathematics 2017-07-01 Human-Robot Interaction and Neuroprosthetics: A review of new technologies Cangelosi, A http://hdl.handle.net/10026.1/9872 10.1109/MCE.2016.2614423 IEEE Consumer Electronics Magazine All content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author. CEMAG-OA-0004-Mar-2016.R3 1 New Technologies for Human Robot Interaction and Neuroprosthetics Angelo Cangelosi, Sara Invitto Abstract—New technologies in the field of neuroprosthetics and These developments in neuroprosthetics are closely linked to robotics are leading to the development of innovative commercial the recent significant investment and progress in research on products based on user-centered, functional processes of cognitive neural networks and deep learning approaches to robotics and neuroscience and perceptron studies. The aim of this review is to autonomous systems [2][3]. Specifically, one key area of analyze this innovative path through the description of some of the development has been that of cognitive robots for human-robot latest neuroprosthetics and human-robot interaction applications, in particular the Brain Computer Interface linked to haptic interaction and assistive robotics. This concerns the design of systems, interactive robotics and autonomous systems. These robot companions for the elderly, social robots for children with issues will be addressed by analyzing developmental robotics and disabilities such as Autism Spectrum Disorders, and robot examples of neurorobotics research. -
Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants
PERSPECTIVE published: 17 July 2017 doi: 10.3389/frobt.2017.00034 Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants Francesco Corucci1,2*, Nick Cheney2,3, Sam Kriegman2, Josh Bongard2 and Cecilia Laschi1 1 The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy, 2 Morphology, Evolution & Cognition Laboratory, University of Vermont, Burlington, VT, United States, 3 Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, United States In this paper, a comprehensive methodology and simulation framework will be reviewed, designed in order to study the emergence of adaptive and intelligent behavior in generic soft-bodied creatures. By incorporating artificial evolutionary and developmental pro- cesses, the system allows to evolve complete creatures (brain, body, developmental properties, sensory, control system, etc.) for different task environments. Whether the Edited by: evolved creatures will resemble animals or plants is in general not known a priori, and Kasper Stoy, IT University of Copenhagen, depends on the specific task environment set up by the experimenter. In this regard, the Denmark system may offer a unique opportunity to explore differences and similarities between Reviewed by: these two worlds. Different material properties can be simulated and optimized, from Dimitris Tsakiris, a continuum of soft/stiff materials, to the interconnection of heterogeneous structures, FORTH Institute of Computer Science, Greece both found in animals and plants alike. The adopted genetic encoding and simulation Naveen Kuppuswamy, environment are particularly suitable in order to evolve distributed sensory and control Toyota Research Institute (TRI), United States systems, which play a particularly important role in plants. -
Evolutionary Developmental Soft Robotics: Towards Adaptive and Intelligent Soft Machines Following Nature's Approach to Design
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/308497541 Evolutionary Developmental Soft Robotics: Towards Adaptive and Intelligent Soft Machines Following Nature's Approach to Design Chapter · September 2017 DOI: 10.1007/978-3-319-46460-2_14 CITATIONS READS 8 287 1 author: Francesco Corucci Scuola Superiore Sant'Anna 24 PUBLICATIONS 355 CITATIONS SEE PROFILE All content following this page was uploaded by Francesco Corucci on 30 October 2017. The user has requested enhancement of the downloaded file. Evolutionary Developmental Soft Robotics: towards adaptive and intelligent soft machines following nature’s approach to design Francesco Corucci Abstract Despite many recent successes in robotics and artificial intelligence, robots are still far from matching the performances of biological creatures outside controlled environments, mainly due to their lack of adaptivity. By taking inspi- ration from nature, bio-robotics and soft robotics have pointed out new directions towards this goal, showing a lot of potential. However, in many ways, this poten- tial is still largely unexpressed. Three main limiting factors can be identified: 1) the common adoption of non-scalable design processes constrained by human capabil- ities, 2) an excessive focus on proximal solutions observed in nature instead of on the natural processes that gave rise to them, 3) the lack of general insights regard- ing intelligence, adaptive behavior, and the conditions under which they emerge in nature. By adopting algorithms inspired by the natural evolution and development, evolutionary developmental soft robotics represents in a way the ultimate form of bio-inspiration. This approach allows the automated design of complete soft robots, whose morphology, control, and sensory system are co-optimized for different tasks and environments, and can adapt in response to environmental stimuli during their lifetime. -
From Motor Learning to Social Learning: a Study of Development on a Humanoid Robot
Abstract From Motor Learning to Social Learning: A Study of Development on a Humanoid Robot In this thesis, we describe how a humanoid robot designed to match the kinematics of a one-year old infant can learn to reach to visual targets, point toward visual targets, and share attention with a human. These three skills span the domains of motor learning and social learning. Instead of developing each of these skills independently, the robot naturally progresses from reaching to pointing and then from pointing to joint attention by taking advantage of social conventions and the assistance of a human. We first present a biologically plausible model for learning to reach to visual targets. This model is then extended to allow the robot to point toward distant objects that are outside of its reach without requiring additional learning. We demonstrate that the development of joint attention can be greatly facilitated by using pointing gestures to actively direct the attention of the robot’s caregiver, resulting in learning times that are two orders of magnitude less than comparable published models and eliminating the need for hand-labeling training data. A dedicated system to evaluate this idea is presented and its performance is demonstrated. From Motor Learning to Social Learning: A Study of Development on a Humanoid Robot A Dissertation Presented to the Faculty of the Graduate School of Yale University in Candidacy for the Degree of Doctor of Philosophy by Ganghua Sun Thesis Advisor: Professor Brian Scassellati July, 2006 °c 2006 by Ganghua Sun. All rights reserved. Contents 1 Introduction 1 1.1 Motivation . -
Comprehensive Review on Modular Self-Reconfigurable Robot Architecture
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 06 Issue: 04 | Apr 2019 www.irjet.net p-ISSN: 2395-0072 Comprehensive Review on Modular Self-Reconfigurable Robot Architecture Muhammad Haziq Hasbulah1, Fairul Azni Jafar2, Mohd. Hisham Nordin2 1Centre for Graduate Studies, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia 2Faculty of Manufacturing Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Self-reconfigurable modular robot is a new film directed by William Don Hall. In this movie, a character approach of robotic system which involves a group of identical named Hiro create a lot of Microbots that able to be robotic modules that are connecting together and forming controlled by neurotransmitter. They are designed by Hiro to structure that able to perform specific tasks. Such robotic connect together to form various shapes and perform tasks system will allows for reconfiguration of the robot and its cooperatively Hall and Williams [3]. The idea of that movie structure in order to adapting continuously to the current concept is multiple robots that able to change shape in group needs or specific tasks, without the use of additional tools. being controlled by human thought. Nowadays, the use of this type of robot is very limited because The MSR robot is build based on the electronics components, it is at the early stage of technology development. This type of computer processors, and memory and power supplies, and robots will probably be widely used in industry, search and also they might have a feature for the robot to have an ability rescue purpose or even on leisure activities in the future. -
Robot Tool Behavior: a Developmental Approach to Autonomous Tool Use
ROBOT TOOL BEHAVIOR: A DEVELOPMENTAL APPROACH TO AUTONOMOUS TOOL USE A Dissertation Presented to The Academic Faculty by Alexander Stoytchev In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in Computer Science College of Computing Georgia Institute of Technology August 2007 Copyright c 2007 by Alexander Stoytchev ROBOT TOOL BEHAVIOR: A DEVELOPMENTAL APPROACH TO AUTONOMOUS TOOL USE Approved by: Ronald Arkin, Advisor Charles Isbell College of Computing College of Computing Georgia Institute of Technology Georgia Institute of Technology Aaron Bobick Harvey Lipkin College of Computing Mechanical Engineering Georgia Institute of Technology Georgia Institute of Technology Tucker Balch College of Computing Georgia Institute of Technology Date Approved: 8 June, 2007 To my late grandfather, who was a carpenter and taught me how to use the tools in his workshop when I was a child. He wanted me to become an architect. I hope that being a roboticist would have been a distant second on his list. iii PREFACE I was fortunate to stumble upon the topic of autonomous tool use in robots for my disserta- tion. When I joined the robotics lab at Georgia Tech I began to look for a good dissertation topic. For almost two years I was reading the robotics literature with that goal in mind. I enjoyed reading but the more I read the more I felt that all the good dissertation topics have already been taken. So I started reading books from other fields of science in hope of finding an inspiration. Finally, the years of reading paid off when I stumbled across Thomas Power's book entitled \Play and Exploration in Children and Animals." At first I was angry at myself for even borrowing a book from the library about children playing with toys (that's what the picture on the front cover showed). -
A Simulated Environment for Developmental Robotics
SEDRo: A Simulated Environment for Developmental Robotics Aishwarya Pothula, Md Ashaduzzaman Rubel Mondol, Sanath Narasimhan, Sm Mazharul Islam, Deokgun Park Computer Science and Engineering University of Texas at Arlington Arlington, Texas USA faishwarya.pothula, mdashaduzzaman.mondol, sanath.narasimhan, [email protected], [email protected] Abstract—Even with impressive advances in application spe- approach had resulted in overfitted solutions that cannot cific models, we still lack knowledge about how to build a model be generalized to diverse tasks. that can learn in a human-like way and do multiple tasks. • Use of refined and focused datasets rather than To learn in a human-like way, we need to provide a diverse experience that is comparable to human’s. In this paper, we diverse and noisy datasets (the first common pattern) introduce our ongoing effort to build a simulated environment for – Because the focus is to teach one skill, we tend to developmental robotics (SEDRo). SEDRo provides diverse human build a refined dataset or an environment that contains experiences ranging from those of a fetus to a 12th month old. only task relevant information. This resulted in spoon-fed A series of simulated tests based on developmental psychology human-edited sensory data [3]. Compare this with how will be used to evaluate the progress of a learning model. We anticipate SEDRo to lower the cost of entry and facilitate research humans learn from unstructured data such as visual and in the developmental robotics community. auditory senses and find underlying structures and apply Index Terms—Baby robots, Sensorimotor development, Em- these structures to many domains [4]. -
AMD Newsletter of the Autonomousnewsletter Mental Development Technical Committee
TheAMD Newsletter of the AutonomousNEWSLETTER Mental Development Technical Committee Developmental Robotics Machine Intelligence Volume 11, number 2 Neuroscience Fall 2014 Psychology Editorial: Learning New Scientific Languages: a Need for Training in Developmental Sciences Understanding sensorimotor, cognitive should always be “experts” of a particular and social development in animals and “discipline”? Maybe not. Disciplines have been robots is a truly interdisciplinary endeavour. created to put some order in the organisation Development happens through the pro- of academic institutions, but as this has had gressive organisation of coupled complex the consequences of building walls between systems, at various spatio-temporal scales, disciplines, disciplines themselves have and covering a large diversity of levels of grown so large that no one can claim to be abstraction, ranging from coupled mechan- an expert in all dimensions of neuroscience, ical dynamics for low-level body control to or biology, or mathematics, or robotics. The higher-level conceptual development. As organisation of research along disciplines Pierre-Yves Oudeyer thinkers like Edgar Morin have been arguing should be replaced by an organisation of for a long time, understanding such complex research around topics, such as “language Inria and Ensta systems in the living requires the combination development”, “body growth” or “sensorim- ParisTech, France of multiple perspectives of analysis, coming otor control”. For each of these topics, some Editor from disciplines as varied as neuroscience, biology (but not all), some physics (but not psychology, robotics, mathematics, physics, all), some neuroscience (but not all), some biology, philosophy, linguistics, anthropology, robotics (but not all) are needed, and what is and primatology. -
Cognitive Robotics to Understand Human Beings
View metadata, citation and similar papers at core.ac.uk brought to you by CORE QUARTERLY REVIEW No.20 / July 2006 1 Cognitive Robotics to Understand Human Beings KAYOKO ISHII Life Science Unit taking place at that time. 1 Introduction In Japan, research on the computational theory of the brain[1] and research combining The question of what human beings (self theory and physiological experiments[2] has been and others), the mind, and the world are has carried out. One of the major themes in Japanese always been of great interest to humankind. brain science in the 1990s was “creating the Most academic disciplines originated to answer brain” beside analytical experimental sciences these questions. As neuroscience has advanced, (“understanding the brain”) and research oriented the notion that brain function is closely related to medical applications (“protecting the brain”). to the mind has become more widely accepted, This theme was significant in that it not only increasing the expectation that unknown aspects expressed the concept of understanding brain of the mind could be explored by neuroscience. functions through “cycles of creation of models of However, a long-standing question regarding the brain, computational theory and neural networks, mind is that one’s mind seems to be associated their verification through experimental science, with oneself as a physical existence, yet its and improvement of theories and models,” but content seems not to be expressed physically. also expressed the unconventional orientation Simply accumulating knowledge acquired of creating new systems inspired by the brain. through external analysis and observation of Furthermore, computational neuroscience was the brain as a physical entity is not sufficient to defined as “to investigate information processing elucidate the essential functions of the brain and of the brain to the extent that artificial machines, the nature of the mind. -
Evolutionary Developmental Robotics – the Next Step to Go?‖
AMD Newsletter Vol. 8, No. 2, 2011 VOLUME 8, NUMBER 2 ISSN 1550-1914 October 2011 Editorial As reported by Minoru Asada as well as by Angelo Cangelosi and Jochen Triesch, the first edition of the joint IEEE ICDL-Epirob in Frankfurt was a real success, gathering many of the usual attendees, as well as newcomers, of the two conferences. It was unanimously decided that the organization of such a joint event should be reproduced next year. Zhengyou Zhang, editor in chief of IEEE TAMD, also just announced that IEEE TAMD was selected for coverage in Thomson Reuter's products and services, beginning with V.1 (1) 2009 (the very first issue). This includes Science Citation Index Expanded, Journal Citation Reports/Science Edition and Neuroscience Citation Index. This month, the newsletter presents a stimulating dialog exploring the frontiers of developmental and evolutionary robotics, within the so-called evo-devo approach which might become more and more central in our research in the future. Yaochu Jin and Yan Meng asked a question about the interaction between phylogeny, ontogeny and epigenesis, as well as about the interaction between morphological and mental development: ―Evolutionary Developmental Robotics – The Next Step to Go?‖. Answers by Josh Bongard, Daniel Polani, Stéphane Doncieux, Fumiya Iida, Nicolas Bredeche, Jean-Marc Montanier, Simon Carrignon, and Gunnar Tufte show that we are just at the beginning of novel far-reaching conceptual and technologi- cal projects, exploring questions such as how development can be the articulation between evolution and learning or how new materials can allow us to explore growing bodies and their impact on cognitive development. -
Developmental Robotics and Its Role Towards Artificial General Intelligence
KI - Künstliche Intelligenz (2021) 35:5–7 https://doi.org/10.1007/s13218-021-00706-w EDITORIAL Developmental Robotics and its Role Towards Artifcial General Intelligence Manfred Eppe1 · Stefan Wermter1 · Verena V. Hafner3 · Yukie Nagai2 Accepted: 13 January 2021 / Published online: 14 February 2021 © The Author(s) 2021 Human intelligence develops through experience, robot computational models that help to understand and to inves- intelligence is engineered – is it? At least in the mainstream tigate embodied cognitive processes. approaches based on classical Artifcial Intelligence (AI) and In this special issue we collect and address several of the Machine Learning (ML) the robotic engineering approach challenges that adhere to the modeling of inductive biases is pursued and data- or knowledge-based algorithms are and developmental robots. In their review, Nguyen et al. [4] designed to improve a robot’s problem-solving performance. provide an overview over the state of the art in modeling the Based on this engineering perspective of classical AI/ML body schema and peripersonal space of robotic agents. The approaches plenty of valuable application-specifc impact authors conclude by proposing a novel theoretical model has been achieved. Yet, the achievements are often subject to learn the peripersonal space and body schema represen- to restrictions that involve domain knowledge as well as con- tations. Other technical contributions include research by straints concerning application domains and computational Hofman et al. [3], who propose a computational model of hardware. the well-known mirror self-recognition test that is deemed Developmental Robotics seeks to extend this constrained to indicate whether animals (e.g.