Journal article Open Access

Affective Robots: Evaluation of Automatic Emotion Recognition Approaches on a Humanoid Robot towards Emotionally Intelligent Machines

Silvia Santano Guillén; Luigi Lo Iacono; Christian Meder

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Silvia Santano Guillén</dc:creator>
  <dc:creator>Luigi Lo Iacono</dc:creator>
  <dc:creator>Christian Meder</dc:creator>
  <dc:description>One of the main aims of current social robotic research
is to improve the robots’ abilities to interact with humans. In order
to achieve an interaction similar to that among humans, robots
should be able to communicate in an intuitive and natural way
and appropriately interpret human affects during social interactions.
Similarly to how humans are able to recognize emotions in other
humans, machines are capable of extracting information from the
various ways humans convey emotions—including facial expression,
speech, gesture or text—and using this information for improved
human computer interaction. This can be described as Affective
Computing, an interdisciplinary field that expands into otherwise
unrelated fields like psychology and cognitive science and involves
the research and development of systems that can recognize and
interpret human affects. To leverage these emotional capabilities
by embedding them in humanoid robots is the foundation of
the concept Affective Robots, which has the objective of making
robots capable of sensing the user’s current mood and personality
traits and adapt their behavior in the most appropriate manner
based on that. In this paper, the emotion recognition capabilities
of the humanoid robot Pepper are experimentally explored, based
on the facial expressions for the so-called basic emotions, as
well as how it performs in contrast to other state-of-the-art
approaches with both expression databases compiled in academic
environments and real subjects showing posed expressions as well
as spontaneous emotional reactions. The experiments’ results show
that the detection accuracy amongst the evaluated approaches differs
substantially. The introduced experiments offer a general structure
and approach for conducting such experimental evaluations. The
paper further suggests that the most meaningful results are obtained
by conducting experiments with real subjects expressing the emotions
as spontaneous reactions.</dc:description>
  <dc:source>International Journal of Mechanical, Industrial and Aerospace Sciences 11.0(6)</dc:source>
  <dc:subject>Affective computing</dc:subject>
  <dc:subject>emotion recognition</dc:subject>
  <dc:subject>Human-Robot-Interaction (HRI)</dc:subject>
  <dc:subject>social robots.</dc:subject>
  <dc:title>Affective Robots: Evaluation of Automatic Emotion Recognition Approaches on a Humanoid Robot towards Emotionally Intelligent Machines</dc:title>
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