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Playing the Emotion Game with Feelix 71

Figure 8.1. Left: Full-body view of Feelix. Right: Children guessing Feelix’s expressions.

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strategy based on the level of emotion activation to select and display the
emotional state of the robot.
To define the “primitives” for each expression we have adopted the fea-
tures concerning positions of eyebrows and lips usually found in the literature,
which can be described in terms of Action Units (AUs) using the Facial Action
Coding System [6]. However, the constraints imposed by the robot’s design
and technology (see [3]) do not permit the exact reproduction of the AUs in-
volved in all of the expressions (e.g., inner brows cannot be raised in Feelix);
in those cases, we adopted the best possible approximation to them, given our
constraints. Feelix’s face is thus much closer to a caricature than to a realistic
model of a human face.
To elicit Feelix’s emotions through tactile stimulation, we have adopted the
generic model postulated by Tomkins [12], which proposes three variants of
a single principle: (1) A sudden increase in the level of stimulation can acti-
vate both positive (e.g., interest) and negative (e.g., startle, fear) emotions; (2)
a sustained high level of stimulation (overstimulation) activates negative emo-
tions such as distress or anger; and (3) a sudden stimulation decrease following
a high stimulation level only activates positive emotions such as joy. We have
complemented Tomkins’ model with two more principles drawn from a home-
ostatic regulation approach to cover two cases that the original model did not
account for: (4) A low stimulation level sustained over time produces negative
emotions such as sadness (understimulation); and (5) a moderate stimulation
level produces positive emotions such as happiness (well-being). Feelix’s emo-
tions, activated by tactile stimulation on the feet, are assigned different inten-
sities calculated on the grounds of stimulation patterns designed on the above
principles. To distinguish between different kinds of stimuli using only binary
touch sensors, we measure the duration and frequency of the presses applied