Abstract: 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.
Abstract: Industrial robots as part of highly automated manufacturing are recently developed to cooperative (light-weight) robots. This offers the opportunity of using them as assistance robots and to improve the participation in professional life of disabled or handicapped people such as tetraplegics. Robots under development are located within a cooperation area together with the working person at the same workplace. This cooperation area is an area where the robot and the working person can perform tasks at the same time. Thus, working people and robots are operating in the immediate proximity. Considering the physical restrictions and the limited mobility of tetraplegics, a hands-free robot control could be an appropriate approach for a cooperative assistance robot. To meet these requirements, the research project MeRoSy (human-robot synergy) develops methods for cooperative assistance robots based on the measurement of head movements of the working person. One research objective is to improve the participation in professional life of people with disabilities and, in particular, mobility impaired persons (e.g. wheelchair users or tetraplegics), whose participation in a self-determined working life is denied. This raises the research question, how a human-robot cooperation workplace can be designed for hands-free robot control. Here, the example of a library scenario is demonstrated. In this paper, an empirical study that focuses on the impact of head movement related stress is presented. 12 test subjects with tetraplegia participated in the study. Tetraplegia also known as quadriplegia is the worst type of spinal cord injury. In the experiment, three various basic head movements were examined. Data of the head posture were collected by a motion capture system; muscle activity was measured via surface electromyography and the subjective mental stress was assessed via a mental effort questionnaire. The muscle activity was measured for the sternocleidomastoid (SCM), the upper trapezius (UT) or trapezius pars descendens, and the splenius capitis (SPL) muscle. For this purpose, six non-invasive surface electromyography sensors were mounted on the head and neck area. An analysis of variance shows differentiated muscular strains depending on the type of head movement. Systematically investigating the influence of different basic head movements on the resulting strain is an important issue to relate the research results to other scenarios. At the end of this paper, a conclusion will be drawn and an outlook of future work will be presented.
Abstract: The recent development of humanoid robots has led robot designers to imagine a great variety of anthropomorphic forms for human-like machine. Which form is the best ? We try to answer this question from a double meaning of the anthropomorphism : a positive anthropomorphism corresponing to the realization of an effective anthropomorphic form object and a negative one corresponding to our natural tendency in certain circumstances to give human attributes to non-human beings. We postulate that any humanoid robot is concerned by both these two anthropomorphism kinds. We propose to use gestalt theory and Heider-s balance theory in order to analyze how negative anthropomorphism can influence our perception of human-like robots. From our theoretical approach we conclude that an “even shape" as defined by gestalt theory is not a sufficient condition for a good integration of future humanoid robots into a human community. Aesthetic perception of the robot cannot be splitted from a social perception : a humanoid robot, any how the efforts made for improving its appearance, could be rejected if it is devoted to a task with too high affective implications.