Achieving fluency through perceptual-symbol practice in human-robot collaboration

ABSTRACT

We have developed a cognitive architecture for robotic teammates based on the neuro-psychological principles of perceptual symbols and simulation, with the aim of attaining increased fluency in human-robot teams. An instantiation of this architecture was implemented on a robotic desk lamp, performing in a human-robot collaborative task. This paper describes initial results from a human-subject study measuring team efficiency and team fluency, in which the robot works on a joint task with untrained subjects. We find significant differences in a number of efficiency and fluency metrics, when comparing our architecture to a purely reactive robot with similar capabilities.

REFERENCES

• 1: L. Barsalou. Perceptual symbol systems. Behavioral and Brain Sciences, 22:577--660, 1999.
• 2: Cynthia Breazeal , Andrew Wang , Rosalind Picard, Experiments with a robotic computer: body, affect and cognition interactions, Proceedings of the ACM/IEEE international conference on Human-robot interaction, March 10-12, 2007, Arlington, Virginia, USA [doi>10.1145/1228716.1228737]
• 3: Christoph Bregler, Learning and Recognizing Human Dynamics in Video Sequences, Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97), p.568, June 17-19, 1997
• 4: Y. Endo. Anticipatory and improvisational robot via recollection and exploitation of episodic memories. In Proceedings of the AAAI Fall Symposium, 2005.
• 5: T. W. Fong, C. Thorpe, and C. Baur. Collaboration, dialogue, and human-robot interaction. In Proceedings of the 10th International Symposium of Robotics Research, Lorne, Victoria, Australia, London, November 2001. Springer-Verlag.
• 6: R. Hamdan, F. Heitz, and L. Thoraval. Gesture localization and recognition using probabilistic visual learning. In Proceedings of the 1999 Conference on Computer Vision and Pattern Recognition (CVPR'99), pages 2098--2103, Ft. Collins, CO, USA, June 1999.
• 7: Guy Hoffman , Cynthia Breazeal, Ensemble: fluency and embodiment for robots acting with humans, Massachusetts Institute of Technology, Cambridge, MA, 2007
• 8: G. Hoffman and C. Breazeal. Collaboration in human-robot teams. In Proc. of the AIAA 1st Intelligent Systems Technical Conference, Chicago, IL, USA, September 2004. AIAA.
• 9: G. Hoffman and C. Breazeal. Robotic partners' bodies and minds: An embodied approach to fluid human-robot collaboration. In Fifth International Workshop on Cognitive Robotics, AAAI'06, 2006.
• 10: G. Hoffman and C. Breazeal. Cost-based anticipatory action-selection for human-robot fluency. IEEE Transactions on Robotics and Automation (in press), 2007.
• 11: H. Jones and S. Rock. Dialogue-based human-robot interaction for space construction teams. In IEEE Aerospace Conference Proceedings, volume 7, pages 3645--3653, 2002.
• 12: O. Khatib, O. Brock, K. Chang, D. Ruspini, L. Sentis, and S. Viji. Human-centered robotics and interactive haptic simulation. International Journal of Robotics Research, 23(2):167--178, February 2004.
• 13: H. Kimura, T. Horiuchi, and K. Ikeuchi. Task-model based human robot cooperation using vision. In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS'99), pages 701--706, 1999.
• 14: G. Lakoff and M. Johnson. Philosophy in the flesh : the embodied mind and its challenge to Western thought. Basic Books, New York, 1999.
• 15: K. Simmons and L. W. Barsalou. The similarity-in-topography principle: Reconciling theories of conceptual deficits. Cognitive Neuropsychology, 20:451--486, 2003.
• 16: M. J. Spivey, D. C. Richardson, and M. Gonzalez-Marquez. On the perceptual-motor and image-schematic infrastructure of language. In D. Pecher and R. A. Zwaan, editors, Grounding cognition: the role of perception and action in memory, language, and thinking. Cambridge Univ. Press, Cambridge, UK, 2005.
• 17: A. Ude, J. Moren, and G. Cheng. Visual attention and distributed processing of visual information for the control of humanoid robots. In M. Hackel, editor, Humanoid Robots: Human-like Machines, chapter 22, pages 423--436. Itech, 2007.
• 18: W. Walker, P. Lamere, P. Kwok, B. Raj, R. Singh, E. Gouvea, P. Wolf, and J. Woelfe. Sphinx-4: A flexible open source framework for speech recognition. Technical Report TR-2004-139, Sun Microsystems Laboratories, November 2004.
• 19: M. Wilson. Six views of embodied cognition. Psychonomic Bulletin & Review, 9(4):625--636, December 2002.
• 20: M. Wilson and G. Knoblich. The case for motor involvement in perceiving conspecifics. Psychological Bulletin, 131:460--473, 2005.
• 21: S. Wilson, A. Saygin, M. Sereno, and M. Iacoboni. Listening to speech activates motor areas involved in speech production. Nature Neuroscience, 7:701--702, 2004.
• 22: H. Woern and T. Laengle. Cooperation between human beings and robot systems in an industrial environment. In Proceedings of the Mechatronics and Robotics, volume 1, pages 156--165, 2000.
• 23: Christopher R. Wren , Brian P. Clarkson , Alex P. Pentland, Understanding Purposeful Human Motion, Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000, p.378, March 26-30, 2000
• 24: C. R. Wren and A. Pentland. Dynaman: A recursive model of human motion. Technical Report VisMod 451, MIT Media Laboratory, 1997.

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.9 Robotics

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods

General Terms:
Algorithms, Experimentation, Human Factors, Performance

Keywords:
anticipation, cognitive architectures, fluency, human subject studies, human-robot interaction, perceptual symbols, robotics, teamwork