Hierarchical action learning by instruction through interactive grounding of body parts and proto-actions

Learning by instruction allows humans programming a robot to achieve a task using spoken language, without the requirement of being able to do the task themselves, which can be problematic for users with motor impairments. We provide a developmental framework to program the humanoid robot iCub without any hand-coded a-priori knowledge about any motor skills. Inspired by child development theories, the system involves hierarchical learning, starting with the human verbally labelling robot body parts. The robot can then focus its attention on a precise body part during robot motor babbling, and link the on-the-fly spoken descriptions of proto-actions to angle values of a specific joint. The direct grounding of proto-actions is possible through the use of a linear model which calculates the effects on the joint of the proto-action and the body part used, allowing a generalisation of the proto-action if the joint has never been used before. Eventually, transferring the grounding is allowed via learning by instructions where humans can combine the newly acquired proto-actions to build primitives and more complex actions by scaffolding them. The framework has been validated using a humanoid robot iCub, which is able to learn without any prior knowledge: 1) the name of its fingers and the corresponding joint number, 2) how to fold and unfold them and 3) how to close or open its hand and how to show numbers with its fingers.

[1]  Michael Felsberg,et al.  Exploratory learning structures in artificial cognitive systems , 2009, Image Vis. Comput..

[2]  A. Meltzoff,et al.  The Robot in the Crib: A Developmental Analysis of Imitation Skills in Infants and Robots. , 2008, Infant and child development.

[3]  Angelo Cangelosi,et al.  Epigenetic Robotics Architecture (ERA) , 2010, IEEE Transactions on Autonomous Mental Development.

[4]  John E. Laird,et al.  The Soar Cognitive Architecture , 2012 .

[5]  Illah R. Nourbakhsh,et al.  A survey of socially interactive robots , 2003, Robotics Auton. Syst..

[6]  Dan Klein,et al.  Grounding spatial relations for human-robot interaction , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  Peter Ford Dominey,et al.  Robot Learning Rules of Games by Extraction of Intrinsic Properties , 2013 .

[8]  Giulio Sandini,et al.  Developmental robotics: a survey , 2003, Connect. Sci..

[9]  Manuela M. Veloso,et al.  Confidence-Based Multi-Robot Learning from Demonstration , 2010, Int. J. Soc. Robotics.

[10]  Peter Ford Dominey,et al.  The Coordinating Role of Language in Real-Time Multimodal Learning of Cooperative Tasks , 2013, IEEE Transactions on Autonomous Mental Development.

[11]  Olivier Mangin,et al.  Learning to recognize parallel combinations of human motion primitives with linguistic descriptions using non-negative matrix factorization , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  Yiannis Aloimonos,et al.  Learning the spatial semantics of manipulation actions through preposition grounding , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[13]  Giulio Sandini,et al.  The iCub humanoid robot: An open-systems platform for research in cognitive development , 2010, Neural Networks.

[14]  Peter Ford Dominey,et al.  Successive Developmental Levels of Autobiographical Memory for Learning Through Social Interaction , 2014, IEEE Transactions on Autonomous Mental Development.

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

[16]  Peter Ford Dominey,et al.  Cooperative human robot interaction systems: IV. Communication of shared plans with Naïve humans using gaze and speech , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[17]  Giorgio Metta,et al.  YARP: Yet Another Robot Platform , 2006 .

[18]  Angelo Cangelosi,et al.  Grounding language in action and perception: from cognitive agents to humanoid robots. , 2010, Physics of life reviews.

[19]  John E. Laird,et al.  Learning Goal-Oriented Hierarchical Tasks from Situated Interactive Instruction , 2014, AAAI.

[20]  B. King.  Social information transfer in monkeys, apes, and hominids , 1994 .

[21]  Aude Billard,et al.  Incremental learning of gestures by imitation in a humanoid robot , 2007, 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[22]  Giulio Sandini,et al.  In Press, Ieee Transactions on Autonomous Mental Development , 2010 .

[23]  Angelo Cangelosi,et al.  An Embodied Model for Sensorimotor Grounding and Grounding Transfer: Experiments With Epigenetic Robots , 2006, Cogn. Sci..

[24]  Maya Cakmak,et al.  Robot Programming by Demonstration with situated spatial language understanding , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[25]  Yiannis Demiris,et al.  Lifelong Augmentation of Multimodal Streaming Autobiographical Memories , 2016, IEEE Transactions on Cognitive and Developmental Systems.

[26]  Y. Demiris,et al.  From motor babbling to hierarchical learning by imitation: a robot developmental pathway , 2005 .

[27]  Henrik Schiøler,et al.  Sociable Robots Through Self-Maintained Energy , 2006 .

[28]  John E. Laird,et al.  Learning Grounded Language through Situated Interactive Instruction , 2012, AAAI Fall Symposium: Robots Learning Interactively from Human Teachers.

[29]  Martina Zambelli,et al.  Online Ensemble Learning of Sensorimotor Contingencies , 2015 .