Abstract
From using forks to eat to maneuvering high-tech gadgets of modern times, humans are adept in swiftly learning to use a wide range of tools in their daily lives. The essence of ‘tool use’ lies in our gradual progression from learning to act ‘on’ objects to learning to act ‘with’ objects in ways to counteract limitations of ‘perceptions, actions and movements’ imposed by our bodies. At the same time, to learn both “cumulatively” and “swiftly” a cognitive agent (human or humanoid) must be able to efficiently integrate multiple streams of information that aid to the learning process itself. Most important among them are social interaction (for example, imitating a teacher’s demonstration), physical interaction (or practice) and “recycling” of previously learnt knowledge (experience) in new contexts. This article presents the skill learning architecture being developed for the humanoid iCub that dynamically integrates multiple streams of learning, multiple task specific constraints and incorporates novel principles that we believe are crucial for constructing a growing motor vocabulary in acting/learning robots. A central feature further is our departure from the well known notion of ‘trajectory formation’ and introduction of the idea of ‘shape’ in the domain of movement. The idea is to learn in an abstract fashion, hence allowing both “task independent” knowledge reuse and task specific “compositionality” to coexist. The scenario of how iCub learns to bimanually coordinate a new tool (a toy crane) to pick up otherwise unreachable objects in its workspace (recycling its past experience of learning to draw) is used to both illustrate central ideas and ask further questions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Visalberghi, E., Tomasello, M.: Primate causal understanding in the physical and in the social domains. Behavioral Processes 42, 189–203 (1997)
Weir, A.A.S., Chappell, J., Kacelnik, A.: Shaping of hooks in New Caledonian Crows. Science 297, 981–983 (2002)
Iriki, A., Sakura, O.: Neuroscience of primate intellectual evolution: natural selection and passive and intentional niche construction. Philos. Trans. R Soc. Lond. B Biol. Sci. 363, 2229–2241 (2008)
Umiltà, M.A., Escola, L., Intskirveli, I., Grammont, F., Rochat, M., Caruana, F., Jezzini, A., Gallese, V., Rizzolatti, G.: When pliers become fingers in the monkey motor system. Proc. Natl. Acad. Sci. USA 105(6), 2209–2213 (2008)
Johnson-Frey, S.H.: The neural bases of complex human tool use. Trends in Cognitive Sciences 8, 71–78 (2004)
Johnson-Frey, S.H., Grafton, S.T.: From ”Acting On” to ” Acting With”: the functional anatomy of action representation. In: Prablanc, C., Pelisson, D., Rossetti, Y. (eds.) Space Coding and Action Production. Elsevier, New York (2003)
Stoytchev, A.: Robot Tool Behavior: A Developmental Approach to Autonomous Tool Use. Ph.D. Dissertation, College of Computing, Georgia Institute of Technology (August 2007)
Stoytchev, A.: Learning the Affordances of Tools Using a Behavior-Grounded Approach. In: Rome, E., Hertzberg, J., Dorffner, G. (eds.) Towards Affordance-Based Robot Control. LNCS (LNAI), vol. 4760, pp. 140–158. Springer, Heidelberg (2008)
Mohan, V., Morasso, P., Metta, G., Sandini, G.: A biomimetic, force-field based computational model for motion planning and bimanual coordination in humanoid robots. Autonomous Robots 27(3), 291–301 (2009)
Mohan, V., Morasso, P.: Passive motion paradigm: an alternative to optimal control. Front. Neurorobot. 5, 4 (2011), doi:10.3389/fnbot.2011.00004
Mohan, V., Morasso, P., Metta, G., Kasderidis, S.: Actions & Imagined Actions in Cognitive robots. In: Cutsuridis, V., Hussain, A., Taylor, J.G. (eds.) Perception-Reason-Action Cycle: Models, Algorithms and Systems. Springer Series in Cognitive and Neural Systems, vol. 1, ch. 17, pp. 539–572 (2011)
Mohan, V., Morasso, P., Zenzeri, J., Metta, G., Chakravarthy, V.S., Sandini, G.: Teaching a humanoid robot to draw ’Shapes’. Autonomous Robots 31(1), 21–53 (2011)
Asatryan, D.G., Feldman, A.G.: Functional tuning of the nervous system with control of movements or maintenance of a steady posture. Biophysics 10, 925–935 (1965)
Hogan, N.: Modularity and Causality in Physical System Modeling. ASME Journal of Dynamic Systems Measurement and Control 109, 384–391 (1987)
Zak, M.: Terminal attractors for addressable memory in neural networks. Phys. Lett. A 133, 218–222 (1988)
Bernstein, N.: The coordination and regulation of movements. Pergamon Press, Oxford (1967)
Shapiro, R.: Direct linear transformation method for three-dimensional cinematography. Res. Quart. 49, 197–205 (1978)
Thom, R.: Structural Stability and Morphogenesis. Addison-Wesley, MA (1975)
Chakravarthy, V.S., Kompella, B.: The shape of handwritten characters. Pattern Recognition Letters (2003)
Maravita, A., Iriki, A.: Tools for the body (schema). Trends in Cognitive Science 8, 79–86 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Mohan, V., Morasso, P. (2012). How Past Experience, Imitation and Practice Can Be Combined to Swiftly Learn to Use Novel “Tools”: Insights from Skill Learning Experiments with Baby Humanoids. In: Prescott, T.J., Lepora, N.F., Mura, A., Verschure, P.F.M.J. (eds) Biomimetic and Biohybrid Systems. Living Machines 2012. Lecture Notes in Computer Science(), vol 7375. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31525-1_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-31525-1_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31524-4
Online ISBN: 978-3-642-31525-1
eBook Packages: Computer ScienceComputer Science (R0)