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A novel affect-sensitive human-robot cooperative framework is presented in this paper. Peripheral physiological indices are measured through wearable biofeedback sensors to detect the affective state of the human. Affect recognition is performed through both quantitative and qualitative analyses. A subsumption control architecture sensitive to the affective state of the human is proposed for a mobile robot. Human-robot cooperation experiments are performed where the robot senses the affective state of the human and responds appropriately. The results presented here validate the proposed framework and demonstrate a new way of achieving implicit communication between a human and a robot.

L. Berkowitz and E. Harmon-Jones (2004) challenge appraisal theories of emotion by describing 2 sets of conditions (physical discomfort and anger-related muscle actions) in which anger appears to be elicited in the absence of theoretically predicted appraisals. In response, the authors discuss the ability of the specific appraisal model they have developed (e.g., C. A. Smith & L. D. Kirby, 2000, 2001; C. A. Smith & R. S. Lazarus, 1990) to account for such instances of anger. First, a number of issues are clarified relevant to the authors' model, including the nature of both the cognitive operations underlying appraisal and the specific appraisals hypothesized to evoke anger. The authors then describe how their model can account for the instances of anger described by L. Berkowitz and E. Harmon-Jones and how both accounts might be tested.

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