D. Angluin, Queries and concept learning, Machine Learning, pp.319-342, 1988.
DOI : 10.1007/BF00116828
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.454.4681

M. Asada, K. Hosoda, Y. Kuniyoshi, H. Ishiguro, T. Inui et al., Cognitive Developmental Robotics: A Survey, IEEE Transactions on Autonomous Mental Development, vol.1, issue.1, 2009.
DOI : 10.1109/TAMD.2009.2021702

B. Bakker and J. Schmidhuber, Hierarchical reinforcement learning based on subgoal discovery and subpolicy specialization, Proc. 8th Conf. on Intelligent Autonomous Systems (IAS-8), 2004.

P. Ball, the Self-Made Tapestry-Pattern formation in nature, 1999.

A. Baranes and P. Oudeyer, R-IAC: Robust Intrinsically Motivated Exploration and Active Learning, IEEE Transactions on Autonomous Mental Development, vol.1, issue.3, pp.155-169, 2009.
DOI : 10.1109/TAMD.2009.2037513
URL : https://hal.archives-ouvertes.fr/hal-00818174

A. Baranes and P. Oudeyer, Intrinsically motivated goal exploration for active motor learning in robots: A case study, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010.
DOI : 10.1109/IROS.2010.5651385
URL : https://hal.archives-ouvertes.fr/inria-00541769

A. Baranes and P. Oudeyer, Maturationally-constrained competence-based intrinsically motivated learning, 2010 IEEE 9th International Conference on Development and Learning, 2010.
DOI : 10.1109/DEVLRN.2010.5578842
URL : https://hal.archives-ouvertes.fr/inria-00541770

A. Baranes and P. Oudeyer, The interaction of maturational constraints and intrinsic motivations in active motor development, 2011 IEEE International Conference on Development and Learning (ICDL), 2011.
DOI : 10.1109/DEVLRN.2011.6037315
URL : https://hal.archives-ouvertes.fr/hal-00646585

A. Baranes and P. Oudeyer, Competence-based intrinsic motivation for active motor learning in robots

A. Barto, S. Singh, C. , and N. , Intrinsically motivated learning of hierarchical collections of skills, Proc. 3rd Int. Conf. Development Learn, pp.112-119, 2004.

L. Berk, Child development, 2008.

D. Berlyne, Conflict, Arousal and Curiosity, 1960.
DOI : 10.1037/11164-000
URL : http://hdl.handle.net/2027/mdp.39015001641003

N. E. Berthier, R. Clifton, D. Mccall, R. , and D. , Proximodistal structure of early reaching in human infants, Experimental Brain Research, vol.127, issue.3, 1999.
DOI : 10.1007/s002210050795

A. Billard, S. Calinon, R. Dillmann, and S. Schaal, Handbook of Robotics, chapter Robot Programming by Demonstration, 2008.

C. M. Bishop, Neural networks for pattern recognition, 1995.

C. M. Bishop, Pattern Recognition and Machine Learning (Information Science and Statistics), 2007.

D. Bjorklund, The role of immaturity in human development., Psychological Bulletin, vol.122, issue.2, pp.153-169, 1997.
DOI : 10.1037/0033-2909.122.2.153

D. Blank, D. Kumar, L. Meeden, M. , and J. , BRINGING UP ROBOT: FUNDAMENTAL MECHANISMS FOR CREATING A SELF-MOTIVATED, SELF-ORGANIZING ARCHITECTURE, Cybernetics and Systems, vol.36, issue.2, 2002.
DOI : 10.1126/science.291.5504.599

R. Brafman and M. Tennenholtz, R-max: A general polynomial time algorithm for near-optimal reinforcement learning, Proceedings of IJCAI'01, 2001.

J. Bremner and A. Slater, Theories of Infant Development, 2003.
DOI : 10.1002/9780470752180

G. Bronson, The Postnatal Growth of Visual Capacity, Child Development, vol.45, issue.4, pp.873-890, 1974.
DOI : 10.2307/1128073

S. Calinon, F. Guenter, and A. Billard, On Learning, Representing, and Generalizing a Task in a Humanoid Robot, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.37, issue.2, 2007.
DOI : 10.1109/TSMCB.2006.886952

R. Castro and R. Novak, Minimax bounds for active learning, IEEE Trans. Information Theory, p.54, 2008.

J. Cazalets, M. Borde, C. , and F. , Localization and organization of the central pattern generator for hindlimb locomotion in newborn rat, Journal of Neuroscience, vol.15, pp.4943-4951, 1995.

T. Cederborg, L. Ming, A. Baranes, and P. Oudeyer, Incremental local online Gaussian Mixture Regression for imitation learning of multiple tasks, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010.
DOI : 10.1109/IROS.2010.5652040
URL : https://hal.archives-ouvertes.fr/inria-00541778

K. Chaloner and I. Verdinelli, Bayesian experimental desing: A review, J. Statistical Science, vol.10, 1995.
DOI : 10.1214/ss/1177009939
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.29.5355

W. Chung, L. Fu, and S. Hsu, Handbook of Robotics, chapter Motion control, pp.133-159, 2008.

D. Cohn, L. Atlas, and R. Ladner, Improving generalization with active learning, Machine Learning, vol.27, issue.4, pp.201-221, 1994.
DOI : 10.1007/BF00993277

D. Cohn, Z. Ghahramani, J. , and M. , Active learning with statistical models, Journal of Artificial Intellifence Research, vol.4, pp.129-145, 1996.

M. Csikszentmihalyi, Creativity-Flow and the Psychology of Discovery and Invention, 1996.

A. Avella, A. Portone, L. Fernandez, and F. Lacquaniti, Control of Fast-Reaching Movements by Muscle Synergy Combinations, Journal of Neuroscience, vol.26, issue.30, pp.7791-7810, 2006.
DOI : 10.1523/JNEUROSCI.0830-06.2006

A. Avella, P. Saltiel, and E. Bizzi, Combinations of muscle synergies in the construction of a natural motor behavior, Nature Neuroscience, vol.6, issue.3, pp.300-308, 2003.
DOI : 10.1038/nn1010

P. Dayan and W. Belleine, Reward, Motivation, and Reinforcement Learning, Neuron, vol.36, issue.2, pp.285-298, 2002.
DOI : 10.1016/S0896-6273(02)00963-7
URL : http://doi.org/10.1016/s0896-6273(02)00963-7

D. Charms and R. , Personal causation: the internal affective determinants of behavior, 1968.

E. Deci and M. Ryan, Intrinsic Motivation and self-determination in human behavior, 1985.
DOI : 10.1007/978-1-4899-2271-7

T. Dick, Y. Oku, J. Romaniuk, C. , and N. , Interaction between central pattern generators for breathing and swallowing in the cat., The Journal of Physiology, vol.465, issue.1, pp.715-730, 1993.
DOI : 10.1113/jphysiol.1993.sp019702

K. Doya, Metalearning and neuromodulation, Neural Networks, vol.15, issue.4-6, pp.4-5, 2002.
DOI : 10.1016/S0893-6080(02)00044-8

J. Eyre, Development and Plasticity of the Corticospinal System in Man, Neural Plasticity, vol.10, issue.1-2, 2003.
DOI : 10.1155/NP.2003.93

D. Faller, U. Klingmller, and J. Timmer, Simulation Methods for Optimal Experimental Design in Systems Biology, SIMULATION, vol.79, issue.12, pp.717-725, 2003.
DOI : 10.1177/0037549703040937

V. Fedorov, Theory of Optimal Experiment, 1972.

L. Festinger, A theory of cognitive dissonance, 1957.

K. Fisher and L. Silvern, Stages and Individual Differences in Cognitive Development, Annual Review of Psychology, vol.36, issue.1, pp.613-648, 1985.
DOI : 10.1146/annurev.ps.36.020185.003145

N. Franceschini, J. Pichon, and C. Blanes, From Insect Vision to Robot Vision [and Discussion], Philosophical Transactions of the Royal Society B: Biological Sciences, vol.337, issue.1281, pp.283-294, 1992.
DOI : 10.1098/rstb.1992.0106

Z. Ghahramani, Solving inverse problems using an em approach to density estimation, Proceedings of the 1993 Connectionist Models Summer School, 1993.

J. Gibson, The ecological approach to visual perception, 1986.

D. H. Grollman and O. C. Jenkins, Incremental learning of subtasks from unsegmented demonstration, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2010.
DOI : 10.1109/IROS.2010.5650500

S. Hart and R. Grupen, Intrinsically motivated hierarchical manipulation, 2008 IEEE International Conference on Robotics and Automation, 2008.
DOI : 10.1109/ROBOT.2008.4543796
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.9133

X. Huang and J. Weng, Novelty and reinforcement learning in the value system of developmental robots, Proceedings of the 2nd international workshop on Epigenetic Robotics : Modeling cognitive development in robotic Pierre-Yves Oudeyer, pp.47-55, 2002.

C. L. Hull, Principles of Behavior, The Journal of Nervous and Mental Disease, vol.101, issue.4, 1943.
DOI : 10.1097/00005053-194504000-00026

J. M. Hunt, Intrinsic motivation and its role in psychological development, Nebraska symposium on motivation, vol.13, pp.189-282, 1965.

F. Iida and R. Pfeifer, Cheap and rapid locomotion of a quadruped robot: Self-stabilization of bounding gait, 2004.

W. James, The principles of psychology, 1890.

M. Johnson, Functional brain development in humans, Nature Reviews Neuroscience, vol.18, issue.7, pp.475-483, 2001.
DOI : 10.1038/35081509

J. Kagan, Motives and development., Journal of Personality and Social Psychology, vol.22, issue.1, pp.51-66, 1972.
DOI : 10.1037/h0032356

S. Kakade and P. Dayan, Dopamine: generalization and bonuses, Neural Networks, vol.15, issue.4-6, pp.549-559, 2002.
DOI : 10.1016/S0893-6080(02)00048-5

F. Kaplan and P. Oudeyer, The progress drive hypothesis: an interpretation of early imitation, Models and mechanisms of imitation and social learning: Behavioural, social and communication dimensions, pp.361-377, 2007.
DOI : 10.1017/CBO9780511489808.024

C. Kemp and A. Edsinger, What can i control?: The development of visual categories for a robots body and the world that it influences, 5th IEEE International Conference on Development and Learning (ICDL-06), Special Session on Autonomous Mental Development, 2006.

O. Khatib, A unified approach for motion and force control of robot manipulators: The operational space formulation, IEEE Journal on Robotics and Automation, vol.3, issue.1, pp.43-53, 1987.
DOI : 10.1109/JRA.1987.1087068

J. Konczak, M. Borutta, and J. Dichgans, The development of goaldirected reaching in infants. learning to produce task-adequate patterns of joint torque, Experimental Brain Research, 1997.

S. Kumar, K. Narasimhan, S. Patwardhan, P. , and V. , Experiment design, identification and control in large-scale chemical processes, Modelling, Identification and Control The 2010 International Conference on, pp.155-160, 2010.

M. Lee, Q. Meng, and F. Chao, Staged Competence Learning in Developmental Robotics, Adaptive Behavior, vol.15, issue.3, pp.241-255, 2007.
DOI : 10.1177/1059712307082085

W. Lee, Neuromotor Synergies as a Basis for Coordinated Intentional Action, Journal of Motor Behavior, vol.50, issue.4, pp.135-170, 1984.
DOI : 10.1080/00222895.1984.10735316

M. Lopes, F. Melo, and L. Montesano, Active Learning for Reward Estimation in Inverse Reinforcement Learning, Proceedings of European Conference on Machine Learning (ECML/PKDD), 2009.
DOI : 10.1007/978-3-642-04174-7_3

M. Lopes and P. Oudeyer, Guest Editorial Active Learning and Intrinsically Motivated Exploration in Robots: Advances and Challenges, IEEE Transactions on Autonomous Mental Development, vol.2, issue.2, pp.65-69, 2010.
DOI : 10.1109/TAMD.2010.2052419
URL : https://hal.archives-ouvertes.fr/inria-00541788

M. Lungarella, G. Metta, R. Pfeifer, and G. Sandini, Developmental robotics: a survey, Connection Science, vol.1, issue.4, pp.151-190, 2003.
DOI : 10.2307/1131322

O. Ly, M. Lapeyre, and P. Oudeyer, Bio-inspired vertebral column, compliance and semi-passive dynamics in a lightweight humanoid robot, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011.
DOI : 10.1109/IROS.2011.6095019

O. Ly and P. Oudeyer, Acroban the humanoid, ACM SIGGRAPH 2010 Emerging Technologies on, SIGGRAPH '10, pp.1-1, 2010.
DOI : 10.1145/1836821.1836825
URL : https://hal.archives-ouvertes.fr/inria-00541786

P. Macneilage, The Origin of Speech, 2008.

A. Meltzoff and M. Moore, Imitation of Facial and Manual Gestures by Human Neonates, Science, vol.198, issue.4312, pp.75-83, 1977.
DOI : 10.1126/science.198.4312.75

J. A. Meyer and S. W. Wilson, A possibility for implementing curiosity and boredom in model-building neural controllers, 1991.

J. Modayil, P. Pilarski, A. White, T. Degris, and R. Sutton, Off-policy knowledge maintenance for robots, Proceedings of Robotics Science and Systems Workshop (Towards Closing the Loop: Active Learning for Robotics), 2010.

K. Montgomery, The role of the exploratory drive in learning., Journal of Comparative and Physiological Psychology, vol.47, issue.1, pp.60-64, 1954.
DOI : 10.1037/h0054833

A. Moore, Fast, robust adaptive control by learning only forward models, Advances in Neural Information Processing Systems 4, 1992.

M. Muja and D. Lowe, Fast approximate nearest neighbors with automatic algorithm, International Conference on Computer Vision Theory and Applications, 2009.

A. Y. Ng and S. Russell, Algorithms for inverse reinforcement learning, Proc. 17th International Conf. on Machine Learning, pp.663-670, 2000.

M. Nguyen, A. Baranes, and P. Oudeyer, Bootstrapping intrinsically motivated learning with human demonstration, 2011 IEEE International Conference on Development and Learning (ICDL), 2011.
DOI : 10.1109/DEVLRN.2011.6037329
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.231.6728

D. Nguyen-tuong and J. Peters, Model learning in robotics: a survey, Cognitive Processing, 2011.

P. Oudeyer, On the Impact of Robotics in Behavioral and Cognitive Sciences: From Insect Navigation to Human Cognitive Development, IEEE Transactions on Autonomous Mental Development, vol.2, issue.1, pp.2-16, 2010.
DOI : 10.1109/TAMD.2009.2039057
URL : https://hal.archives-ouvertes.fr/inria-00541783

P. Oudeyer and F. Kaplan, Discovering communication, Connection Science, vol.66, issue.2, pp.189-206, 2006.
DOI : 10.1080/09540090600768567
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.100.8192

P. Oudeyer and F. Kaplan, What is intrinsic motivation? A typology of computational approaches, Frontiers in Neurorobotics, vol.1, issue.6, 2007.
DOI : 10.3389/neuro.12.006.2007

P. Oudeyer and F. Kaplan, How can we define intrinsic motivations ?, Proc. Of the 8th Conf. On Epigenetic Robotics, 2008.

P. Oudeyer, F. Kaplan, and V. Hafner, Intrinsic Motivation Systems for Autonomous Mental Development, IEEE Transactions on Evolutionary Computation, vol.11, issue.2, pp.265-286, 2007.
DOI : 10.1109/TEVC.2006.890271

P. Oudeyer, O. Ly, R. , and P. , Exploring robust, intuitive and emergent physical human-robot interaction with the humanoid robot Acroban, 2011 11th IEEE-RAS International Conference on Humanoid Robots, 2011.
DOI : 10.1109/Humanoids.2011.6100852
URL : https://hal.archives-ouvertes.fr/hal-00652126

C. Paul, Morphology and computation, Proceedings of the International Conference on the Simulation of Adaptive Behaviour, 2004.

J. Peters and S. Schaal, Natural actor critic, Neurocomputing, pp.7-91180, 2008.
DOI : 10.1016/j.neucom.2007.11.026

R. Pfeifer and J. C. Bongard, How the Body Shapes the Way We Think: A New View of, Intelligence, 2006.

R. Pfeifer, M. Lungarella, and F. Iida, Self-Organization, Embodiment, and Biologically Inspired Robotics, Science, vol.318, issue.5853, pp.1088-1093, 2007.
DOI : 10.1126/science.1145803
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.377.1611

R. Pfeifer and C. Scheier, Understanding intelligence, 1999.

J. Piaget, The Origins of Intelligence in Childhood, 1952.

M. Ring, Continual Learning in Reinforcement Environments, 1994.

P. Rochat, Object manipulation and exploration in 2- to 5-month-old infants., Developmental Psychology, vol.25, issue.6, pp.871-884, 1989.
DOI : 10.1037/0012-1649.25.6.871

M. Rolf, J. Steil, and M. Gienger, Goal Babbling Permits Direct Learning of Inverse Kinematics, IEEE Transactions on Autonomous Mental Development, vol.2, issue.3, pp.216-229, 2010.
DOI : 10.1109/TAMD.2010.2062511

R. M. Ryan and E. L. Deci, Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions, Contemporary Educational Psychology, vol.25, issue.1, pp.54-67, 2000.
DOI : 10.1006/ceps.1999.1020
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.318.808

S. Schaal and C. G. Atkeson, Robot juggling: an implementation of memory-based learning. Control systems magazine, pp.57-71, 1994.

S. Schaal and C. G. Atkeson, Robot learning by nonparametric regression, pp.137-153, 1995.

M. Schembri, M. Mirolli, and G. Baldassare, Evolving internal reinforcers for an intrinsically motivated reinforcement-learning robot, 2007 IEEE 6th International Conference on Development and Learning, 2007.
DOI : 10.1109/DEVLRN.2007.4354052

M. Schembri, M. Mirolli, G. , and B. , Evolution and Learning in an Intrinsically Motivated Reinforcement Learning Robot, Advances in Artificial Life. Proceedings of the 9th European Conference on Artificial Life, pp.294-333, 2007.
DOI : 10.1007/978-3-540-74913-4_30

M. Schlesinger, Heterochrony: It's (all) about time! In, Proceedings of the Eighth International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, pp.111-117, 2008.

J. Schmidhuber, Curious model-building control systems, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks, pp.1458-1463, 1991.
DOI : 10.1109/IJCNN.1991.170605

J. Schmidhuber, Exploring the Predictable, Advances in Evolutionary Computing: theory and applications, pp.579-612, 2002.
DOI : 10.1007/978-3-642-18965-4_23

J. Schmidhuber, Developmental robotics, optimal artificial curiosity, creativity, music, and the fine arts, Connection Science, vol.1, issue.2, 2006.
DOI : 10.1080/09540090600768658

J. Schmidhuber, Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990–2010), IEEE Transactions on Autonomous Mental Development, vol.2, issue.3, pp.230-247, 2010.
DOI : 10.1109/TAMD.2010.2056368

J. Scholz, M. Klein, T. Behrens, and H. Johansen-berg, Training induces changes in white-matter architecture, Nature Neuroscience, vol.31, issue.11, pp.1367-1368, 2009.
DOI : 10.1038/nn.2412

O. Sigaud, C. Salan, and V. Padois, On-line regression algorithms for learning mechanical models of robots: A survey, Robotics and Autonomous Systems, vol.59, issue.12, 2011.
DOI : 10.1016/j.robot.2011.07.006
URL : https://hal.archives-ouvertes.fr/hal-00629133

S. Singh, R. Lewis, A. Barto, and J. Sorg, Intrinsically Motivated Reinforcement Learning: An Evolutionary Perspective, IEEE Transactions on Autonomous Mental Development, vol.2, issue.2, pp.70-82, 2010.
DOI : 10.1109/TAMD.2010.2051031
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.180.1045

A. Stout and A. Barto, Competence based intrinsic motivation, Proceedings of IEEE International Conference on Development and Learning, 2010.
DOI : 10.1109/devlrn.2010.5578835
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.224.71

R. Sutton, Integrated architectures for learning, planning, and reacting based on approximating integrated architectures for learning, planning, and reacting based on approximating dynamic programming, Proceedings of the Pierre-Yves Oudeyer, Adrien Baranes, Frédéric Kaplan International Machine Learning Conference, pp.212-218, 1990.

R. Sutton and A. Barto, Reinforcement Learning: An Introduction, IEEE Transactions on Neural Networks, vol.9, issue.5, 1998.
DOI : 10.1109/TNN.1998.712192

R. Sutton, D. Precup, and S. Singh, Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning, Artificial Intelligence, vol.112, issue.1-2, pp.181-211, 1999.
DOI : 10.1016/S0004-3702(99)00052-1

I. Szita and A. Lorincz, The many faces of optimism, Proceedings of the 25th international conference on Machine learning, ICML '08, 2008.
DOI : 10.1145/1390156.1390288

A. Thomaz and C. Breazeal, Experiments in socially guided exploration: lessons learned in building robots that learn with and without human teachers, Connection Science, vol.1, issue.2-3, pp.91-110, 2008.
DOI : 10.1016/j.artint.2007.09.009

S. Thrun, The role of exploration in learning control, Handbook for Intelligent Control: Neural, Fuzzy and Adaptive Approaches, 1992.

S. Thrun and K. Moller, Active exploration in dynamic environments, 1992.

L. Ting and J. Mckay, Neuromechanics of muscle synergies for posture and movement, Current Opinion in Neurobiology, vol.17, issue.6, pp.622-628, 2007.
DOI : 10.1016/j.conb.2008.01.002

S. Tong and E. Chang, Support vector machine active learning for image retrieval, Proceedings of the ninth ACM international conference on Multimedia , MULTIMEDIA '01, pp.107-118, 2001.
DOI : 10.1145/500141.500159

G. Turkewitz and P. Kenny, The Role of Developmental Limitations of Sensory Input on Sensory/Perceptual Organization, Journal of Developmental & Behavioral Pediatrics, vol.6, issue.5, pp.302-308, 1985.
DOI : 10.1097/00004703-198510000-00014

E. Weiss and M. Flanders, Muscular and Postural Synergies of the Human Hand, Journal of Neurophysiology, vol.92, issue.1, pp.523-535, 2004.
DOI : 10.1152/jn.01265.2003

J. Weng, J. Mcclelland, A. Pentland, O. Sporns, I. Stockman et al., Autonomous mental development by robots and animals, Science, pp.291599-600, 2001.

R. White, Motivation reconsidered: The concept of competence., Psychological Review, vol.66, issue.5, pp.297-333, 1959.
DOI : 10.1037/h0040934

S. Whitehead, A study of cooperative mechanisms for faster reinforcement learning. Tr-365, 1991.

M. Wiering and J. Schmidhuber, HQ-Learning, Adaptive Behavior, vol.3, issue.2, pp.219-246, 1997.
DOI : 10.1177/105971239700600202

W. Wundt, Grundzuge der Physiologischen Psychologie, The American Journal of Psychology, vol.6, issue.2, 1874.
DOI : 10.2307/1410982
URL : https://babel.hathitrust.org/cgi/imgsrv/download/pdf?id=umn.31951000932490f;orient=0;size=100;seq=9;attachment=0

H. Yokoi, A. Hernandez, R. Katoh, W. Yu, I. Watanabe et al., Embodied artificial intelligence, chapter Mutual adaptation in a prosthetics application, 2004.

M. Ziegler, F. Iida, and R. Pfeifer, Cheap underwater locomotion: roles of morphological properties and behavioural diversity, Proc. Int. Conf. on Climbing and Walking Robots, 2006.