Psychophysiological control architecture for human-robot coordination-concepts and initial experiments

The use of robots is expected to be pervasive in many spheres of society: in hospitals, homes, offices and battlefields, where the robots will need to interact and cooperate closely with a variety of people. The paper proposes an innovative approach to human-robot cooperation where the robot will be able to recognize the psychological state of the interacting human and modify its (i.e., robot's) own action to make the human feel comfortable in working with the robot. Wearable biofeedback sensors are used to measure a variety of physiological indices to infer the underlying psychological states (affective states) of the human. The eventual idea is to correlate the psychological states with the actions of the robot to determine which action(s) is responsible for a particular affective state. The robot controller will then modify that action if there is a need to alter the affective state. A concept of such a control architecture, a requirement analysis, and initial results from human experiments for stress detection are presented.

[1]  R. Plutchik A GENERAL PSYCHOEVOLUTIONARY THEORY OF EMOTION , 1980 .

[2]  R. Brooks,et al.  The cog project: building a humanoid robot , 1999 .

[3]  Jennifer Healey,et al.  Affective wearables , 1997, Digest of Papers. First International Symposium on Wearable Computers.

[4]  Elias Vyzas Recognition of emotional and cognitive states using physiological data , 1999 .

[5]  J. Cacioppo,et al.  Inferring psychological significance from physiological signals. , 1990, The American psychologist.

[6]  V. Borkar,et al.  A unified framework for hybrid control: model and optimal control theory , 1998, IEEE Trans. Autom. Control..

[7]  R. Levenson Autonomic Nervous System Differences among Emotions , 1992 .

[8]  Bruce Blumberg,et al.  The Art and Science of Synthetic Character Design , 1999 .

[9]  Rosalind W. Picard Affective Computing , 1997 .

[10]  P. Ekman,et al.  Autonomic nervous system activity distinguishes among emotions. , 1983, Science.

[11]  Li-Xin Wang,et al.  A Course In Fuzzy Systems and Control , 1996 .

[12]  Gabriella Cincotti,et al.  Frequency decomposition and compounding of ultrasound medical images with wavelet packets , 2001, IEEE Transactions on Medical Imaging.

[13]  Jennifer Healey,et al.  Digital processing of affective signals , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[14]  Brian Scassellati,et al.  Infant-like Social Interactions between a Robot and a Human Caregiver , 2000, Adapt. Behav..

[15]  S. Tomkins The positive affects , 1963 .

[16]  Illah R. Nourbakhsh,et al.  Robot improv: using drama to create believable agents , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[17]  Andrew Ortony,et al.  The Cognitive Structure of Emotions , 1988 .