The New Robotics—towards Human-centered Machines

Research in robotics has moved away from its primary focus on industrial applications. The New Robotics is a vision that has been developed in past years by our own university and many other national and international research institutions and addresses how increasingly more human‐like robots can live among us and take over tasks where our current society has shortcomings. Elder care, physical therapy, child education, search and rescue, and general assistance in daily life situations are some of the examples that will benefit from the New Robotics in the near future. With these goals in mind, research for the New Robotics has to embrace a broad interdisciplinary approach, ranging from traditional mathematical issues of robotics to novel issues in psychology, neuroscience, and ethics. This paper outlines some of the important research problems that will need to be resolved to make the New Robotics a reality.

[1]  J. Piaget Play, dreams and imitation in childhood , 1951 .

[2]  M. Mead,et al.  Cybernetics , 1953, The Yale Journal of Biology and Medicine.

[3]  M. Ciletti,et al.  The computation and theory of optimal control , 1972 .

[4]  G. Johansson Visual perception of biological motion and a model for its analysis , 1973 .

[5]  Elliot Saltzman,et al.  Levels of sensorimotor representation , 1979 .

[6]  John H. R. Maunsell,et al.  Hierarchical organization and functional streams in the visual cortex , 1983, Trends in Neurosciences.

[7]  S Ullman,et al.  Shifts in selective visual attention: towards the underlying neural circuitry. , 1985, Human neurobiology.

[8]  Michael A. Arbib,et al.  Schema theory , 1998 .

[9]  Oussama Khatib,et al.  A unified approach for motion and force control of robot manipulators: The operational space formulation , 1987, IEEE J. Robotics Autom..

[10]  David J. Reinkensmeyer,et al.  Model-based robot learning , 1988 .

[11]  S. Grossberg,et al.  Neural dynamics of planned arm movements: emergent invariants and speed-accuracy properties during trajectory formation. , 1988, Psychological review.

[12]  J. Taylor,et al.  Playing safe? , 1989, Nursing times.

[13]  Yoshihiko Nakamura,et al.  Advanced robotics - redundancy and optimization , 1990 .

[14]  Tad McGeer,et al.  Passive Dynamic Walking , 1990, Int. J. Robotics Res..

[15]  P. Viviani,et al.  A developmental study of the relationship between geometry and kinematics in drawing movements. , 1991, Journal of experimental psychology. Human perception and performance.

[16]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[17]  Christopher G. Atkeson,et al.  What should be learned , 1992 .

[18]  M. Tomasello,et al.  Imitative learning of actions on objects by children, chimpanzees, and enculturated chimpanzees. , 1993, Child development.

[19]  A. Meltzoff,et al.  Imitation, Memory, and the Representation of Persons. , 1994, Infant behavior & development.

[20]  Stefan Schaal,et al.  Robot learning by nonparametric regression , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[21]  J. Braun Visual search among items of different salience: removal of visual attention mimics a lesion in extrastriate area V4 , 1994, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[22]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[23]  Bruno Siciliano,et al.  Modeling and Control of Robot Manipulators , 1995 .

[24]  Michael A. Arbib,et al.  The handbook of brain theory and neural networks , 1995, A Bradford book.

[25]  S. Schaal,et al.  A Kendama Learning Robot Based on Bi-directional Theory , 1996, Neural Networks.

[26]  Daniel M. Wolpert,et al.  Forward Models for Physiological Motor Control , 1996, Neural Networks.

[27]  Mitsuo Kawato,et al.  Equilibrium-Point Control Hypothesis Examined by Measured Arm Stiffness During Multijoint Movement , 1996, Science.

[28]  S. Kajita,et al.  Experimental study of biped dynamic walking , 1996 .

[29]  E. Taub,et al.  Constraint Induced Movement Techniques To Facilitate Upper Extremity Use in Stroke Patients. , 1997, Topics in stroke rehabilitation.

[30]  P. Viviani,et al.  Perceiving and tracking kinesthetic stimuli: further evidence of motor-perceptual interactions. , 1997, Journal of experimental psychology. Human perception and performance.

[31]  Yasuo Kuniyoshi,et al.  Deferred imitation of human head movements by an active stereo vision head , 1997, Proceedings 6th IEEE International Workshop on Robot and Human Communication. RO-MAN'97 SENDAI.

[32]  Oussama Khatib,et al.  Load Independence of the Dynamically Consistent Inverse of the Jacobian Matrix , 1997, Int. J. Robotics Res..

[33]  Joseph A. Driscoll,et al.  A visual attention network for a humanoid robot , 1998, Proceedings. 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No.98CH36190).

[34]  Mitsuo Kawato,et al.  A tennis serve and upswing learning robot based on bi-directional theory , 1998, Neural Networks.

[35]  Akira Ito,et al.  An attention-based approach to symbol acquisition , 1998, Proceedings of the 1998 IEEE International Symposium on Intelligent Control (ISIC) held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA) Intell.

[36]  A. Goldman,et al.  Mirror neurons and the simulation theory of mind-reading , 1998, Trends in Cognitive Sciences.

[37]  M. Arbib,et al.  Language within our grasp , 1998, Trends in Neurosciences.

[38]  D M Wolpert,et al.  Multiple paired forward and inverse models for motor control , 1998, Neural Networks.

[39]  R. Byrne,et al.  Priming primates: Human and otherwise , 1998, Behavioral and Brain Sciences.

[40]  M. Matarić Behavior-based robotics as a tool for synthesis of artificial behavior and analysis of natural behavior , 1998, Trends in Cognitive Sciences.

[41]  Daniel E. Koditschek,et al.  Sequential Composition of Dynamically Dexterous Robot Behaviors , 1999, Int. J. Robotics Res..

[42]  Gregor Schöner,et al.  The uncontrolled manifold concept: identifying control variables for a functional task , 1999, Experimental Brain Research.

[43]  Mitsuo Kawato,et al.  Internal models for motor control and trajectory planning , 1999, Current Opinion in Neurobiology.

[44]  B. Scassellati Imitation and mechanisms of joint attention: a developmental structure for building social skills on a humanoid robot , 1999 .

[45]  J. H. van der Lee,et al.  Forced use of the upper extremity in chronic stroke patients: results from a single-blind randomized clinical trial. , 1999, Stroke.

[46]  Dariu Gavrila,et al.  The Visual Analysis of Human Movement: A Survey , 1999, Comput. Vis. Image Underst..

[47]  S. Wolf,et al.  An application of upper-extremity constraint-induced movement therapy in a patient with subacute stroke. , 1999, Physical therapy.

[48]  Constantine Stephanidis,et al.  Universal access in the information society , 1999, HCI.

[49]  Stefan Schaal,et al.  Is imitation learning the route to humanoid robots? , 1999, Trends in Cognitive Sciences.

[50]  Christof Koch,et al.  Comparison of feature combination strategies for saliency-based visual attention systems , 1999, Electronic Imaging.

[51]  Jake K. Aggarwal,et al.  Human Motion Analysis: A Review , 1999, Comput. Vis. Image Underst..

[52]  Philip N. Sabes,et al.  The planning and control of reaching movements , 2000, Current Opinion in Neurobiology.

[53]  C. Koch,et al.  A saliency-based search mechanism for overt and covert shifts of visual attention , 2000, Vision Research.

[54]  Jon Rigelsford,et al.  Modelling and Control of Robot Manipulators , 2000 .

[55]  Andrew Y. Ng,et al.  Pharmacokinetics of a novel formulation of ivermectin after administration to goats , 2000, ICML.

[56]  Maja J. Mataric,et al.  Getting Humanoids to Move and Imitate , 2000, IEEE Intell. Syst..

[57]  Stefan Schaal,et al.  Real Time Learning in Humanoids: A challenge for scalability of Online Algorithms , 2000 .

[58]  Joshua G. Hale,et al.  Using Humanoid Robots to Study Human Behavior , 2000, IEEE Intell. Syst..

[59]  G. Loeb Learning from the spinal cord , 2001, The Journal of physiology.

[60]  C. Koch,et al.  Computational modelling of visual attention , 2001, Nature Reviews Neuroscience.

[61]  Mitsuo Kawato,et al.  MOSAIC Model for Sensorimotor Learning and Control , 2001, Neural Computation.

[62]  Brian Scassellati,et al.  Active vision for sociable robots , 2001, IEEE Trans. Syst. Man Cybern. Part A.

[63]  Stefan Schaal,et al.  Overt visual attention for a humanoid robot , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[64]  Stefan Schaal,et al.  Biomimetic Oculomotor Control , 2001, Adapt. Behav..

[65]  Lynne E. Parker,et al.  Multi-Robot Systems: From Swarms to Intelligent Automata , 2002, Springer Netherlands.

[66]  Oliver Brock,et al.  Robotics and interactive simulation , 2002, CACM.

[67]  C. Breazeal,et al.  Robots that imitate humans , 2002, Trends in Cognitive Sciences.

[68]  Mitsuo Kawato,et al.  Multiple Model-Based Reinforcement Learning , 2002, Neural Computation.

[69]  Gillian M. Hayes,et al.  Imitation as a dual-route process featuring prediction and learning components: A biologically plaus , 2002 .

[70]  Jun Nakanishi,et al.  Learning Attractor Landscapes for Learning Motor Primitives , 2002, NIPS.

[71]  Kazuhito Yokoi,et al.  UKEMI: falling motion control to minimize damage to biped humanoid robot , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[72]  Stefan Schaal,et al.  Learning Robot Control , 2002 .

[73]  Michael I. Jordan,et al.  Optimal feedback control as a theory of motor coordination , 2002, Nature Neuroscience.

[74]  Brian Scassellati,et al.  Theory of Mind for a Humanoid Robot , 2002, Auton. Robots.

[75]  M. Sakaguchi Robo sapiens : Evolution of a New Species , 2002 .

[76]  Giulio Sandini,et al.  Learning visual stabilization reflexes in robots with moving eyes , 2002, Neurocomputing.

[77]  David S. Touretzky,et al.  Long-Term Reward Prediction in TD Models of the Dopamine System , 2002, Neural Computation.

[78]  K. Dautenhahn,et al.  Imitation in Animals and Artifacts , 2002 .

[79]  K. Doya,et al.  A unifying computational framework for motor control and social interaction. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[80]  Sridhar Mahadevan,et al.  Recent Advances in Hierarchical Reinforcement Learning , 2003, Discret. Event Dyn. Syst..

[81]  Stefan Schaal,et al.  Reinforcement Learning for Humanoid Robotics , 2003 .

[82]  R. Johansson,et al.  Action plans used in action observation , 2003, Nature.

[83]  Stefan Schaal,et al.  http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained , 2007 .

[84]  Kenji Doya,et al.  Meta-learning in Reinforcement Learning , 2003, Neural Networks.

[85]  Laurent Itti,et al.  Realistic avatar eye and head animation using a neurobiological model of visual attention , 2004, SPIE Optics + Photonics.

[86]  Jun Nakanishi,et al.  Learning Movement Primitives , 2005, ISRR.

[87]  M. Kawato,et al.  Adaptation to Stable and Unstable Dynamics Achieved By Combined Impedance Control and Inverse Dynamics Model , 2003 .

[88]  Gordon Cheng,et al.  Learning from Observation and from Practice Using Behavioral Primitives , 2003, ISRR.

[89]  Maja J. Matarić,et al.  Data-driven derivation of skills for autonomous humanoid agents , 2003 .

[90]  Sethu Vijayakumar,et al.  Scaling Reinforcement Learning Paradigms for Motor Learning , 2003 .

[91]  D. Wolpert,et al.  Decoding, imitating and influencing the actions of others: the mechanisms of social interaction - Introduction , 2003 .

[92]  O. Khatib TASK-ORIENTED CONTROL OF HUMANOID ROBOTS THROUGH PRIORITIZATION , 2004 .

[93]  M. Kawato,et al.  Optimal impedance control for task achievement in the presence of signal-dependent noise. , 2004, Journal of neurophysiology.

[94]  Gordon Cheng,et al.  Learning tasks from observation and practice , 2004, Robotics Auton. Syst..

[95]  John Kenneth Salisbury,et al.  Playing it safe [human-friendly robots] , 2004, IEEE Robotics & Automation Magazine.

[96]  Andrew W. Moore,et al.  Locally Weighted Learning for Control , 1997, Artificial Intelligence Review.

[97]  Stefan Schaal,et al.  Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning , 2002, Applied Intelligence.

[98]  Andrew W. Moore,et al.  Locally Weighted Learning , 1997, Artificial Intelligence Review.

[99]  E. J. Cheng,et al.  Measured and modeled properties of mammalian skeletal muscle. II. The effectsof stimulus frequency on force-length and force-velocity relationships , 1999, Journal of Muscle Research & Cell Motility.

[100]  D. Wolpert,et al.  The neuroscience of social interaction : decoding, imitating, and influencing the actions of others , 2004 .

[101]  Yoshihiko Nakamura,et al.  Embodied Symbol Emergence Based on Mimesis Theory , 2004, Int. J. Robotics Res..

[102]  Oussama Khatib,et al.  Whole-Body Dynamic Behavior and Control of Human-like Robots , 2004, Int. J. Humanoid Robotics.

[103]  Tetsuo Ono,et al.  Development and evaluation of interactive humanoid robots , 2004, Proceedings of the IEEE.

[104]  Gordon Cheng,et al.  Discovering optimal imitation strategies , 2004, Robotics Auton. Syst..

[105]  Mitsuo Kawato,et al.  A theory for cursive handwriting based on the minimization principle , 1995, Biological Cybernetics.

[106]  G. Loeb,et al.  Measured and modeled properties of mammalian skeletal muscle. I. The effects of post-activation potentiation on the time course and velocity dependencies of force production , 1999, Journal of Muscle Research & Cell Motility.

[107]  K. Doya,et al.  Cerebellar aminergic neuromodulation: towards a functional understanding , 2004, Brain Research Reviews.

[108]  Jeff Weber,et al.  MERTZ: a quest for a robust and scalable active vision humanoid head robot , 2004, 4th IEEE/RAS International Conference on Humanoid Robots, 2004..

[109]  Sean R Eddy,et al.  What is dynamic programming? , 2004, Nature Biotechnology.

[110]  Suguru Arimoto,et al.  Natural resolution of ill-posedness of inverse kinematics for redundant robots: a challenge to Bernstein's degrees-of-freedom problem , 2005, Adv. Robotics.

[111]  S. Schaal,et al.  Computational motor control in humans and robots , 2005, Current Opinion in Neurobiology.

[112]  Aude Billard,et al.  Robotic assistants in therapy and education of children with autism: can a small humanoid robot help encourage social interaction skills? , 2005, Universal Access in the Information Society.

[113]  L. Itti,et al.  Modeling the influence of task on attention , 2005, Vision Research.

[114]  Lynne E. Parker,et al.  Multi-Robot Systems. From Swarms to Intelligent Automata Volume III , 2005 .

[115]  Alin Albu-Schäffer,et al.  A Unified Passivity-based Control Framework for Position, Torque and Impedance Control of Flexible Joint Robots , 2007, Int. J. Robotics Res..

[116]  Jun Nakanishi,et al.  A Unifying Framework for the Control of Robotic Systems , 2005 .

[117]  Christopher K. I. Williams How to Pretend That Correlated Variables Are Independent by Using Difference Observations , 2005, Neural Computation.

[118]  Oliver Brock,et al.  A Framework for Learning and Control in Intelligent Humanoid Robots , 2005, Int. J. Humanoid Robotics.

[119]  Richard S. Sutton,et al.  Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.

[120]  Stefan Schaal,et al.  A New Methodology for Robot Controller Design , 2005 .

[121]  Stefan Schaal,et al.  Incremental Online Learning in High Dimensions , 2005, Neural Computation.

[122]  Emanuel Todorov,et al.  Stochastic Optimal Control and Estimation Methods Adapted to the Noise Characteristics of the Sensorimotor System , 2005, Neural Computation.

[123]  Russ Tedrake,et al.  Efficient Bipedal Robots Based on Passive-Dynamic Walkers , 2005, Science.

[124]  Stefan Schaal,et al.  Natural Actor-Critic , 2003, Neurocomputing.

[125]  Adam Jacoff,et al.  RoboCup 2005: Robot Soccer World Cup IX , 2006, RoboCup.

[126]  Minoru Asada,et al.  Human-Inspired Robots , 2006, IEEE Intelligent Systems.

[127]  Stefan Schaal,et al.  Learning Operational Space Control , 2006, Robotics: Science and Systems.

[128]  M. Mon-Williams,et al.  Motor Control and Learning , 2006 .

[129]  Ludovic Righetti,et al.  Design Methodologies for Central Pattern Generators: An Application to Crawling Humanoids , 2006, Robotics: Science and Systems.

[130]  M. Arbib Action to language via the mirror neuron system , 2006 .

[131]  Stefan Schaal Action to Language via the Mirror Neuron System: Dynamic systems: brain, body, and imitation , 2006 .

[132]  Miles C. Bowman,et al.  Control strategies in object manipulation tasks , 2006, Current Opinion in Neurobiology.

[133]  L. Itti,et al.  Visual causes versus correlates of attentional selection in dynamic scenes , 2006, Vision Research.

[134]  Jun Nakanishi,et al.  Inverse Dynamics Control with Floating Base and Constraints , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[135]  S. Schaal The Computational Neurobiology of Reaching and Pointing — A Foundation for Motor Learning by Reza Shadmehr and Steven P. Wise , 2007 .