Long-term human—robot interaction, especially in the case of humanoid robots, requires an adaptable and varied behavior base. In this paper, we present a method for capturing, or learning, sequential tasks by transferring serial behavior execution from deliberative to routine control. The incorporation of this approach leads to the natural development of complex and varied behaviors, with lower demands for planning, coordination and resources. We demonstrate how this process can be performed autonomously as part of the normal function of the robot, without the need for an explicit learning stage or user guidance. The complete implementation of this algorithm on the Sony QRIO humanoid robot is described.
Arkin, R., Fujita, M., Takagi, T., & Hasegawa, R. (2003). An ethological basis for human—robot interaction. Robotics and AutonomousSystems, 42(3—4), 191—201.
2.
Badgalyan, R. (2000). Executive control, willed actions, and non-conscious processing. Human Brain Mapping, 9(38), 38—41.
3.
Cisek, P. (2001). Embodiment is all in the head. Behavioral and Brain Sciences, 24(1), 36—38.
4.
Cleeremans, A. (1993). Mechanisms of implicit learning: Connectionist models of sequence processing. Cambridge, MA: MIT Press.
5.
Cooper, R.P., & Glasspool, D.W. (2001). Learning action affordances and action schemas. In R. M. French & J. P. Sougne (Eds.), Perspectives in neural computing (pp. 133—142). Berlin: Springer.
6.
Cooper, R., & Shallice, T. (1997). Modeling the selection of routine action: Exploring the criticality of parameter values. In Proceedings of the 19th Annual Conference of the Cognitive Science Society (pp. 130—135). Stanford University, CA.
7.
Cooper, R., & Shallice, T. (2000). Contention scheduling and the control of routine activities. Cognitive Neuropsychology, 17(4), 297—338.
8.
Cooper, R., Shallice, T., & Farringdon, J. (1995). Symbolic and continuous processes in the automatic selection of actions. Hybrid Problems, Hybrid Solutions, 2, 27—37.
9.
Fujita, M., Kuroki, Y., Ishida, T., & Doi, T. (2003). Autonomous behavior control architecture of entertainment humanoid robot SDR-4X. In Proceedings of the IEEE/RSJ international Conference on Intelligent Robots and Systems.Las Vegas, NV.
10.
Garforth, J., Meehan, A., & McHale, S. (2000). Attentional behavior in robotic agents. In Proceedings of the International Workshop on Recent Advances in Mobile Robots. Leicester, UK.
11.
Hoshino, Y., Takagi, T., Profio, U., & Fujita, M. (2004). Behavior description and control using behavior module for personal robot. In Proceedings of the IEEE International Conference on Robotics and AutomationNew Orleans, LA.
12.
Houghton, G., & Hartley, T. (1995). Parallel models of serial behaviour: Lashley revisited . Psyche, 2(25).
13.
Keele, S., Ivry, R., Mayr, E., Hazeltine, E., & Heuer, H. (2004). The cognitive and neural architecture of sequence representation. Psychological Review, 110, 316—339.
14.
Lashley, K.S. (1951). The problem of serial order in behavior. In L. Jeffress (Ed.), Cerebral mechanisms in behavior. New York: Wiley.
15.
Norman, D.A., & Shallice, T. (1986). Consciousness and self-regulation: Advances in theory and research. In D. S. R. Davidson & G. Schwartz (Eds.), Attention to action: willed and automatic control of behavior (Vol. 4, pp. 515— 549). New York: Academic Press.
16.
Prescott, T., Gurney, K., & Redgrave, P. (2003). Basal ganglia. In M. A. Arbib (Ed.), The handbook of brain theory and neural networks (2nd ed.). Cambridge, MA: MIT Press.
17.
Sawada, T., Takagi, T., & Fujita, M. (2004a). Behavior selection and motion modulation in emotionally grounded architecture for QRIO SDR-4X II. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems . Sendai, Japan.
18.
Sawada, T., Takagi, T., Hoshino, Y., & Fujita, M. (2004b). Learning behavior selection through interaction based on emotionally grounded symbol concept. In Proceedings of the IEEE-RAS/RSJ International Conference on Humanoid Robots . Los Angeles, CA.
19.
Sun, R., & Giles, L. (2001). Sequence learning: Paradigms, algorithms, and applications. Berlin: Springer.
20.
Tanaka, F., Noda, K., Sawada, T., & Fujita, M. (2004). Associated emotion and its expression in an entertainment robot QRIO. In Proceedings of the International Conference on Entertainment Computing (pp. 499—504). Eindhoven , the Netherlands.
21.
Ulam, P., & Arkin, R. (2006). Biasing behavioral activation with intent (Technical Report No. GIT-GVU-06-11). Graphics, Visualization, and Usability (GVU) Center, Georgia Institute of Technology.
