Skilled motor behavior is critical in many human daily life activities and professions. The design of robots that can effectively teach motor skills is an important challenge in the robotics field. In particular, it is important to understand whether the involvement in the training of a robot exhibiting social behaviors impacts on the learning and the experience of the human pupils. In this study, we addressed this question and we asked participants to learn a complex task -stabilizing an inverted pendulum -by training with physical assistance provided by a robotic manipulandum, the Wristbot. One group of participants performed the training only using the Wristbot, whereas for another group the same physical assistance was attributed to the humanoid robot iCub, who played the role of an expert trainer and exhibited also some social behaviors. The results obtained show that participants of both groups effectively acquired the skill by leveraging the physical assistance, as they significantly improved their stabilization performance even when the assistance was removed. Moreover, learning in a context of interaction with a humanoid robot assistant led subjects to increased motivation and more enjoyable training experience, without negative effects on attention and perceived effort. With the experimental approach presented in this study, it is possible to investigate the relative contribution of haptic and social signals in the context of motor learning mediated by human-robot interaction, with the aim of developing effective robot trainers.
During the interaction with others, action, speech, and touches can communicate positive, neutral, or negative attitudes. Offering an apple can be gentle or rude, a caress can be kind or rushed. These subtle aspects of social communication have been named vitality forms by Daniel Stern. Although they characterize all human interactions, to date it is not clear whether vitality forms expressed by an agent may affect the action perception and the motor response of the receiver. To this purpose, we carried out a psychophysics study aiming to investigate how perceiving different vitality forms can influence cognitive and motor tasks performed by participants. In particular, participants were stimulated with requests made through a physical contact or vocally and conveying rude or gentle vitality forms, and then they were asked to estimate the end of a passing action observed in a monitor (action estimation task) or to perform an action in front of it (action execution task) with the intention to pass an object to the other person presented in the video. Results of the action estimation task indicated that the perception of a gentle request increased the duration of a rude action subsequently observed, while the perception of a rude request decreased the duration of the same action performed gently. Additionally, during the action execution task, accordingly with the perceived vitality form, participants modulated their motor response.
Effective tutoring during motor learning requires to provide the appropriate physical assistance to the learners, but at the same time to assess and adapt to their state, to avoid frustration. With the aim of endowing robot tutors with these abilities, we designed an experiment in which participants had to acquire a new motor ability -balancing an unstable inverted pendulum -with the support of a robot providing fixed physical assistance. We analyzed participants' behavior and explicit evaluations to (i) identify the motor strategy associated with best performances in the task; (ii) assess whether natural facial expressions automatically extracted from cameras during task execution can inform about the participant's state. The results indicate that the variation and the mean of the wrist velocity are the most relevant in the effective balancing strategy, suggesting that a robot tutor could reorient the attention of the pupil on this parameter to facilitate the learning process. Moreover, facial expressions vary significantly during the task, especially in the dimension of Valence, which decreases with training. Interestingly, only when the robot had an anthropomorphic presence, Valence correlated with the degree of frustration experienced in the task. These findings highlight that both physical behavior and affective signals could be integrated by an autonomous robot to generate adaptive and individualized assistance, mindful both of the learning process and the partner's affective state.
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