Sensorimotor Learning for an Artificial Body Schema on Humanoid Robots

zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften der Fakultat fur Informatik des Karlsruher Instituts fur Technologie (KIT).

[1]  Klaus Schulten,et al.  Motion planning of a pneumatic robot using a neural network , 1997 .

[2]  Tamim Asfour,et al.  Improving Body Schema Learning with Kinematic Bézier Maps by Symmetry Constraints , 2013 .

[3]  A. Liegeois,et al.  Automatic supervisory control of the configuration and behavior of multi-body mechanisms , 1977 .

[4]  S. Schaal,et al.  Robot juggling: implementation of memory-based learning , 1994, IEEE Control Systems.

[5]  Christian Laugier,et al.  Growing Hidden Markov Models: An Incremental Tool for Learning and Predicting Human and Vehicle Motion , 2009, Int. J. Robotics Res..

[6]  D. Wolpert,et al.  When Feeling Is More Important Than Seeing in Sensorimotor Adaptation , 2002, Current Biology.

[7]  Wolfram Burgard,et al.  Body Schema Learning , 2012, Towards Service Robots for Everyday Environments.

[8]  Carl E. Rasmussen,et al.  Gaussian processes for machine learning , 2005, Adaptive computation and machine learning.

[9]  A. Maravita,et al.  Tools for the body (schema) , 2004, Trends in Cognitive Sciences.

[10]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[11]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[12]  F. Vignemont.  Body schema and body image—Pros and cons , 2010, Neuropsychologia.

[13]  Pietro G. Morasso,et al.  Do Humanoid Robots Need a Body Schema? , 2012, BICA.

[14]  Giulio Sandini,et al.  Sensorimotor Interaction in a Developing Robot , 2001 .

[15]  Giulio Sandini,et al.  The iCub humanoid robot: an open platform for research in embodied cognition , 2008, PerMIS.

[16]  Helge J. Ritter,et al.  Self-Organizing Feature Maps for Modeling and Control of Robotic Manipulators , 2003, J. Intell. Robotic Syst..

[17]  V. Ramachandran,et al.  Projecting sensations to external objects: evidence from skin conductance response , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[18]  Pietro Morasso,et al.  WHAT IS THE USE OF THE BODY SCHEMA FOR HUMANOID ROBOTS , 2013 .

[19]  Alexander Stoytchev,et al.  Learning the Affordances of Tools Using a Behavior-Grounded Approach , 2006, Towards Affordance-Based Robot Control.

[20]  Masaki Ogino,et al.  Body Image Constructed from Motor and Tactile Images with Visual Information , 2007, Int. J. Humanoid Robotics.

[21]  Francis L. Merat,et al.  Introduction to robotics: Mechanics and control , 1987, IEEE J. Robotics Autom..

[22]  Olivier Sigaud,et al.  On-line regression algorithms for learning mechanical models of robots: A survey , 2011, Robotics Auton. Syst..

[23]  M. Tanaka,et al.  Coding of modified body schema during tool use by macaque postcentral neurones. , 1996, Neuroreport.

[24]  Martin V. Butz,et al.  Learning velocity kinematics: Experimental comparison of on-line regression algorithms , 2012 .

[25]  Michael I. Jordan,et al.  Forward Models: Supervised Learning with a Distal Teacher , 1992, Cogn. Sci..

[26]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[27]  Minoru Asada,et al.  Cognitive developmental robotics as a new paradigm for the design of humanoid robots , 2001, Robotics Auton. Syst..

[28]  Mark Fiala,et al.  ARTag, a fiducial marker system using digital techniques , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[29]  J. F. Soechting,et al.  Errors in pointing are due to approximations in sensorimotor transformations. , 1989, Journal of neurophysiology.

[30]  John M. Hollerbach,et al.  Autonomous Robot Calibration for Hand-Eye Coordination , 1991, Int. J. Robotics Res..

[31]  William A. Gruver,et al.  Kinematic control of redundant robots and the motion optimizability measure , 2001, IEEE Trans. Syst. Man Cybern. Part B.

[32]  Dana Kulic,et al.  Online learning of inverse dynamics via Gaussian Process Regression , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[33]  Kenneth Kreutz-Delgado,et al.  Canonical parameterization of excess motor degrees of freedom with self-organizing maps , 1996, IEEE Trans. Neural Networks.

[34]  Minoru Asada,et al.  Real-Time Inverse Dynamics Learning for Musculoskeletal Robots based on Echo State Gaussian Process Regression , 2012, Robotics: Science and Systems.

[35]  F. Flentge,et al.  Locally Weighted Interpolating Growing Neural Gas , 2006, IEEE Transactions on Neural Networks.

[36]  Yuichi Kobayashi,et al.  Planning-Space Shift Motion Generation: Variable-space Motion Planning Toward Flexible Extension of Body Schema , 2011, J. Intell. Robotic Syst..

[37]  Helge J. Ritter,et al.  An instantaneous topological mapping model for correlated stimuli , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

[38]  W. Boehm,et al.  Bezier and B-Spline Techniques , 2002 .

[39]  Jenq-Neng Hwang,et al.  Neural network architectures for robotic applications , 1989, IEEE Trans. Robotics Autom..

[40]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[41]  Alessandro Farnè,et al.  Grab an object with a tool and change your body: tool-use-dependent changes of body representation for action , 2012, Experimental Brain Research.

[42]  C Rorden,et al.  When a rubber hand 'feels' what the real hand cannot. , 1999, Neuroreport.

[43]  Lehel Csató,et al.  Sparse On-Line Gaussian Processes , 2002, Neural Computation.

[44]  Günter Hommel,et al.  On the Tangent-Half-Angle Substitution , 1993 .

[45]  Shrikanth S. Narayanan,et al.  Statistical methods for estimation of direct and differential kinematics of the vocal tract , 2013, Speech Commun..

[46]  P. Morasso,et al.  Kinematic networks , 1988, Biological Cybernetics.

[47]  Tamim Asfour,et al.  ARMAR-III: An Integrated Humanoid Platform for Sensory-Motor Control , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.

[48]  Giulio Sandini,et al.  Learning to Exploit Proximal Force Sensing: A Comparison Approach , 2010, From Motor Learning to Interaction Learning in Robots.

[49]  Carme Torras,et al.  Using PSOMs to Learn Inverse Kinematics Through Virtual Decomposition of the Robot , 2005, IWANN.

[50]  A. Hall,et al.  Adaptive Switching Circuits , 2016 .

[51]  Jivko Sinapov,et al.  Toward Autonomous Learning of an Ontology of Tool Affordances by a Robot , 2008, AAAI.

[52]  D. Wolpert,et al.  Internal models in the cerebellum , 1998, Trends in Cognitive Sciences.

[53]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[54]  Klaus Schulten,et al.  Topology-conserving maps for learning visuo-motor-coordination , 1989, Neural Networks.

[55]  Thomas Martinetz,et al.  A neural network for robot control: cooperation between neural units as a requirement for learning , 1993 .

[56]  Pietro G. Morasso,et al.  Towards Reasoning and Coordinating Action in the Mental Space , 2007, Int. J. Neural Syst..

[57]  Giorgio Metta,et al.  Incremental learning of robot dynamics using random features , 2011, 2011 IEEE International Conference on Robotics and Automation.

[58]  Christopher G. Atkeson,et al.  Constructive Incremental Learning from Only Local Information , 1998, Neural Computation.

[59]  Jun Wang,et al.  A primal-dual neural network for online resolving constrained kinematic redundancy in robot motion control , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[60]  John M. Hollerbach,et al.  The Calibration Index and Taxonomy for Robot Kinematic Calibration Methods , 1996, Int. J. Robotics Res..

[61]  Stefan Ulbrich,et al.  Learning robot dynamics with Kinematic Bézier Maps , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[62]  D. Wolpert,et al.  Disorders of Body Scheme , 2004 .

[63]  Aude Billard,et al.  Online Learning of the Body Schema , 2008, Int. J. Humanoid Robotics.

[64]  Marco Antonelli,et al.  Implicit Sensorimotor Mapping of the Peripersonal Space by Gazing and Reaching , 2011, IEEE Transactions on Autonomous Mental Development.

[65]  N. A. Bernshteĭn.  The co-ordination and regulation of movements , 1967 .

[66]  Yasuo Kuniyoshi,et al.  A Method for Sustaining Consistent Sensory–Motor Coordination under Body Property Changes Including Tool Grasp/Release , 2010, Adv. Robotics.

[67]  G. Sandini,et al.  A developmental approach to grasping , 2004 .

[68]  Giulio Sandini,et al.  A biomimetic, force-field based computational model for motion planning and bimanual coordination in humanoid robots , 2009, Auton. Robots.

[69]  Stefan Ulbrich,et al.  General Robot Kinematics Decomposition Without Intermediate Markers , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[70]  Jean-Claude Gilhodes,et al.  A neural network model for the intersensory coordination involved in goal-directed movements , 1991, Biological Cybernetics.

[71]  Martin V. Butz,et al.  Controlling a Four Degree of Freedom Arm in 3D Using the XCSF Learning Classifier System , 2009, KI.

[72]  Stefan Schaal,et al.  Memory-based robot learning , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[73]  J. Friedman,et al.  A Statistical View of Some Chemometrics Regression Tools , 1993 .

[74]  Gordon Cheng,et al.  Online learning of a motor map for humanoid robot reaching , 2003 .

[75]  Miao‐kun Sun,et al.  Trends in cognitive sciences , 2012 .

[76]  Giorgio Metta,et al.  Actions and Imagined Actions in Cognitive Robots , 2011 .

[77]  José Santos-Victor,et al.  Visual transformations in gesture imitation: what you see is what you do , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[78]  Minoru Asada,et al.  Is it my body? Body extraction from uninterpreted sensory data based on the invariance of multiple sensory attributes , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[79]  Jochen J. Steil,et al.  Goal Babbling Permits Direct Learning of Inverse Kinematics , 2010, IEEE Transactions on Autonomous Mental Development.

[80]  Gordon Cheng,et al.  Dexterous Skills Transfer by Extending Human Body Schema to a Robotic Hand , 2006, 2006 6th IEEE-RAS International Conference on Humanoid Robots.

[81]  Bernhard Schölkopf,et al.  Learning Inverse Dynamics: a Comparison , 2008, ESANN.

[82]  Yiannis Demiris,et al.  A nonparametric Bayesian approach toward robot learning by demonstration , 2012, Robotics Auton. Syst..

[83]  M. Farah,et al.  The psychological reality of the body schema: a test with normal participants. , 1995, Journal of experimental psychology. Human perception and performance.

[84]  Alejandro Hernández Arieta,et al.  Body Schema in Robotics: A Review , 2010, IEEE Transactions on Autonomous Mental Development.

[85]  Stefan Klanke,et al.  PSOM+ : Parametrized Self-Organizing Maps for noisy and incomplete data , 2005 .

[86]  Dana Kulic,et al.  Learning inverse dynamics for redundant manipulator control , 2010, 2010 International Conference on Autonomous and Intelligent Systems, AIS 2010.

[87]  Tamim Asfour,et al.  Human-like motion of a humanoid robot arm based on a closed-form solution of the inverse kinematics problem , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

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

[89]  Atsushi Iriki,et al.  Self-images in the video monitor coded by monkey intraparietal neurons , 2001, Neuroscience Research.

[90]  Bernhard Schölkopf,et al.  Sparse online model learning for robot control with support vector regression , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[91]  P. Morasso,et al.  Self-Organizing Body Schema for Motor Planning , 1995 .

[92]  José Santos-Victor,et al.  Visual learning by imitation with motor representations , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[93]  Jörg A. Walter.  Rapid learning in robotics , 1996 .

[94]  Nicholas P. Holmes,et al.  Does tool use extend peripersonal space? A review and re-analysis , 2012, Experimental Brain Research.

[95]  V. Braitenberg.  Vehicles, Experiments in Synthetic Psychology , 1984 .

[96]  Brigitte Röder,et al.  The body in a multisensory world , 2012 .

[97]  Stefan Schaal,et al.  Locally Weighted Projection Regression : An O(n) Algorithm for Incremental Real Time Learning in High Dimensional Space , 2000 .

[98]  Alessia Tessari,et al.  Motor distal component and pragmatic representation of objects. , 2002, Brain research. Cognitive brain research.

[99]  C. Spence,et al.  Multisensory integration and the body schema: close to hand and within reach , 2003, Current Biology.

[100]  Dana Kulic,et al.  Online Incremental Learning of Inverse Dynamics Incorporating Prior Knowledge , 2011, AIS.

[101]  Stefan Schaal,et al.  Local Dimensionality Reduction , 1997, NIPS.

[102]  Aude Billard,et al.  On Learning, Representing, and Generalizing a Task in a Humanoid Robot , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[103]  A. Billard,et al.  Iterative Estimation of Rigid-Body Transformations Application to Robust Object Tracking and Iterative Closest Point , 2010 .

[104]  Eugenio Faldella,et al.  A neural approach to robotic haptic recognition of 3-D objects based on a Kohonen self-organizing feature map , 1997, IEEE Trans. Ind. Electron..

[105]  Takeo Kanade,et al.  Automated Construction of Robotic Manipulation Programs , 2010 .

[106]  M. Lungarella,et al.  Towards a model for tool-body assimilation and adaptive tool-use , 2007, 2007 IEEE 6th International Conference on Development and Learning.

[107]  Stefan Ulbrich,et al.  Rapid learning of humanoid body schemas with Kinematic Bézier Maps , 2009, 2009 9th IEEE-RAS International Conference on Humanoid Robots.

[108]  Giorgio Metta,et al.  Grounding vision through experimental manipulation , 2003, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[109]  G. Rizzolatti,et al.  Object representation in the ventral premotor cortex (area F5) of the monkey. , 1997, Journal of neurophysiology.

[110]  Peter I. Corke,et al.  Robotics, Vision and Control - Fundamental Algorithms in MATLAB® , 2011, Springer Tracts in Advanced Robotics.

[111]  Patrick van der Smagt,et al.  Neural Network Control of a Pneumatic Robot Arm , 1994, IEEE Trans. Syst. Man Cybern. Syst..

[112]  J. Massion,et al.  BODY SCHEMA AND BODY IMAGE-A DOUBLE DISSOCIATION IN DEAFFERENTED PATIENTS , 2003 .

[113]  Pietro G. Morasso,et al.  How Past Experience, Imitation and Practice Can Be Combined to Swiftly Learn to Use Novel "Tools": Insights from Skill Learning Experiments with Baby Humanoids , 2012, Living Machines.

[114]  M. Arbib,et al.  Sensorimotor learning , 1998 .

[115]  C. Gross,et al.  A bimodal map of space: somatosensory receptive fields in the macaque putamen with corresponding visual receptive fields , 1993, Experimental Brain Research.

[116]  Manuel Lopes,et al.  Robot Manifolds for Direct and Inverse Kinematics Solutions , 2007 .

[117]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[118]  Maxim I. Stamenov,et al.  Body schema, body image, and mirror neurons , 2005 .

[119]  E. Menzel.  Animal Tool Behavior: The Use and Manufacture of Tools by Animals, Benjamin B. Beck. Garland STPM Press, New York and London (1980), 306, Price £24.50 , 1981 .

[120]  Jörg A. Walter.  PSOM network: learning with few examples , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[121]  Oliver Brock,et al.  Learning to Manipulate Articulated Objects in Unstructured Environments Using a Grounded Relational Representation , 2008, Robotics: Science and Systems.

[122]  C. Sammut,et al.  An Architecture for Tool Use and Learning in Robots , 2007 .

[123]  Stefan Schaal,et al.  Learning inverse kinematics , 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).

[124]  Martin V. Butz,et al.  Context-dependent predictions and cognitive arm control with XCSF , 2008, GECCO '08.

[125]  Olivier Sigaud,et al.  Control of redundant robots using learned models: An operational space control approach , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[126]  Ronald C. Arkin,et al.  Robot tool behavior: a developmental approach to autonomous tool use , 2007 .

[127]  Manuel Lopes,et al.  Body schema acquisition through active learning , 2010, 2010 IEEE International Conference on Robotics and Automation.

[128]  Stefan Ulbrich,et al.  OpenGRASP: A Toolkit for Robot Grasping Simulation , 2010, SIMPAR.

[129]  Yasuo Kuniyoshi,et al.  Adaptive body schema for robotic tool-use , 2006, Adv. Robotics.

[130]  Shuuji Kajita,et al.  Cybernetic human HRP-4C , 2009, 2009 9th IEEE-RAS International Conference on Humanoid Robots.

[131]  Jonathan D. Cohen,et al.  Rubber hands ‘feel’ touch that eyes see , 1998, Nature.

[132]  Zoubin Ghahramani,et al.  Solving inverse problems using an EM approach to density estimation , 1993 .

[133]  Manuel Lopes,et al.  A learning framework for generic sensory-motor maps , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[134]  Helge J. Ritter,et al.  Visual recognition of continuous hand postures , 2002, IEEE Trans. Neural Networks.

[135]  Martin V. Butz,et al.  Learning sensorimotor control structures with XCSF: redundancy exploitation and dynamic control , 2009, GECCO '09.

[136]  Stefan Ulbrich,et al.  Kinematic Bézier Maps , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[137]  Masaki Ogino,et al.  Cross-modal body representation based on visual attention by saliency , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[138]  Maria V. Sanchez-Vives,et al.  Extending Body Space in Immersive Virtual Reality: A Very Long Arm Illusion , 2012, PloS one.

[139]  A. Benton,et al.  Right-left discrimination and finger localization : development and pathology , 1960 .

[140]  David Vernon,et al.  Using neural networks to learn hand-eye co-ordination , 1994, Neural Computing & Applications.

[141]  Santanu Chaudhury,et al.  Self-organizing neural networks for learning inverse dynamics of robot manipulator , 1995, Proceedings of IEEE/IAS International Conference on Industrial Automation and Control.

[142]  G. Metta,et al.  Learning precise 3D reaching in a humanoid robot , 2007, 2007 IEEE 6th International Conference on Development and Learning.

[143]  Tamim Asfour,et al.  ARMAR-4: A 63 DOF torque controlled humanoid robot , 2013, 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).

[144]  Giulio Sandini,et al.  A developmental approach to visually-guided reaching in artificial systems , 1999, Neural Networks.

[145]  Jochen J. Steil,et al.  Bootstrapping inverse kinematics with Goal Babbling , 2010, 2010 IEEE 9th International Conference on Development and Learning.

[146]  Jan Peters,et al.  Model learning for robot control: a survey , 2011, Cognitive Processing.

[147]  J. Gerstmann.  PROBLEM OF IMPERCEPTION OF DISEASE AND OF IMPAIRED BODY TERRITORIES WITH ORGANIC LESIONS RELATION TO BODY SCHEME AND ITS DISORDERS , 1942 .

[148]  Stefan Schaal,et al.  Real-time robot learning with locally weighted statistical learning , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[149]  JamesW. Lewis.  Cortical Networks Related to Human Use of Tools , 2006, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

[150]  S. Aglioti,et al.  The body in the brain revisited , 2009, Experimental Brain Research.

[151]  Gerald Farin,et al.  NURBS: From Projective Geometry to Practical Use , 1999 .

[152]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[153]  Radford M. Neal.  Pattern Recognition and Machine Learning , 2007, Technometrics.

[154]  John M. Hollerbach,et al.  A Recursive Lagrangian Formulation of Maniputator Dynamics and a Comparative Study of Dynamics Formulation Complexity , 1980, IEEE Transactions on Systems, Man, and Cybernetics.

[155]  Wolfram Burgard,et al.  Body schema learning for robotic manipulators from visual self-perception , 2009, Journal of Physiology - Paris.

[156]  G. Holmes,et al.  Sensory disturbances from cerebral lesions , 1911 .

[157]  Jochen J. Steil,et al.  Learning Flexible Full Body Kinematics for Humanoid Tool Use , 2010, 2010 International Conference on Emerging Security Technologies.

[158]  Giulio Sandini,et al.  A Neural Framework for Organization and Flexible Utilization of Episodic Memory in Cumulatively Learning Baby Humanoids , 2014, Neural Computation.

[159]  Olivier Sigaud,et al.  Learning the velocity kinematics of ICUB for model-based control: XCSF versus LWPR , 2011, 2011 11th IEEE-RAS International Conference on Humanoid Robots.

[160]  Carme Torras,et al.  Self-calibration of a space robot , 1997, IEEE Trans. Neural Networks.

[161]  Helge J. Ritter,et al.  Rapid learning with parametrized self-organizing maps , 1996, Neurocomputing.

[162]  Helge J. Ritter,et al.  Neural computation and self-organizing maps - an introduction , 1992, Computation and neural systems series.

[163]  J. Friedman,et al.  [A Statistical View of Some Chemometrics Regression Tools]: Response , 1993 .

[164]  Thomas A Carlson,et al.  Tool Integration and Dynamic Touch , 2013, Psychological science.

[165]  Minoru Asada,et al.  Body Scheme Acquisition by Cross Modal Map Learning among Tactile, Visual, and Proprioceptive Spaces , 2002 .

[166]  Hiroaki Gomi,et al.  Contraction of body representation induced by proprioceptive conflict , 2009, Current Biology.

[167]  Alexander Stoytchev,et al.  Computational Model for an Extendable Robot Body Schema , 2003 .

[168]  Valentina Rastelli,et al.  Tool-use reshapes the boundaries of body and peripersonal space representations , 2013, Experimental Brain Research.

[169]  J.M. Hollerbach,et al.  Identifying mass parameters for gravity compensation and automatic torque sensor calibration , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[170]  Carme Torras,et al.  Speeding up the learning of robot kinematics through function decomposition , 2005, IEEE Transactions on Neural Networks.

[171]  Minoru Asada,et al.  Unique association between self-occlusion and double-touching towards binding vision and touch , 2007, Neurocomputing.

[172]  Giulio Sandini,et al.  Development: Is it the right way towards humanoid robotics? , 2001 .

[173]  Martin V. Butz,et al.  A comparative study: function approximation with LWPR and XCSF , 2010, GECCO '10.

[174]  David R. Rowland.  The brain that changes itself: Stories of personal triumph from the frontiers of brain science , 2010 .

[175]  Daniel E. Whitney,et al.  Resolved Motion Rate Control of Manipulators and Human Prostheses , 1969 .

[176]  Giulio Sandini,et al.  Autonomous learning of 3D reaching in a humanoid robot , 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[177]  Carme Torras,et al.  Learning Inverse Kinematics: Reduced Sampling Through Decomposition Into Virtual Robots , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[178]  José Santos-Victor,et al.  Learning Sensory-Motor Maps for Redundant Robots , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[179]  Jean-Pierre Merlet.  Interval Analysis for Certified Numerical Solution of Problems in Robotics , 2009, Int. J. Appl. Math. Comput. Sci..

[180]  Richard Bellman,et al.  Directions of Mathematical Research in Nonlinear Circuit Theory , 1960 .

[181]  H. Cruse,et al.  On the cost functions for the control of the human arm movement , 1990, Biological Cybernetics.

[182]  J. Lackner.  Some proprioceptive influences on the perceptual representation of body shape and orientation. , 1988, Brain : a journal of neurology.

[183]  Stefan Schaal,et al.  Local Dimensionality Reduction for Non-Parametric Regression , 2009, Neural Processing Letters.

[184]  Giulio Sandini,et al.  Teaching a humanoid robot to draw ‘Shapes’ , 2011, Auton. Robots.