324 research outputs found
A Gaze-contingent Dictating Robot to Study Turn-taking
No full textSciutti A, Schillingmann L, Palinko O, Nagai Y, Sandini G. A Gaze-contingent Dictating Robot to Study Turn-taking. Presented at the 10th ACM/IEEE International Conference on Human-Robot Interaction
Gaze contingency in turn-taking for human robot interaction: Advantages and drawbacks
No full textPalinko O, Sciutti A, Schillingmann L, Rea F, Nagai Y, Sandini G. Gaze Contingency in Turn-Taking for Human Robot Interaction: Advantages and Drawbacks. Presented at the 24th IEEE International Symposium on Robot and Human Interactive Communication
Multimodal Emotion Recognition of Hand-Object Interaction
No full textIn this paper, we investigate whether information related to touches and rotations impressed to an object can be effectively used to classify the emotion of the agent manipulating it. We specifically focus on sequences of basic actions (e.g., grasping, rotating), which are constituents of daily interactions. We use the iCube, a 5 cm cube covered with tactile sensors and embedded with an accelometer, to collect a new dataset including 11 persons performing action sequences associated with 4 emotions: Anger, sadness, excitement and gratitude. Next, we propose 17 high-level hand-crafted features based on the tactile and kinematics data derived from the iCube. Twelve of these features vary significantly as a function of the emotional context in which the action sequence was performed. In particular, a larger surface of the object is engaged in physical contact for anger and excitement, than for sadness. Furthermore, the average duration of interactions labeled as sad, is longer than for the remaining 3 emotions. More rotations are performed for anger and excitement than for sadness and gratitude. The accuracy of a classification experiment in the case of four emotions reaches 0.75. This result shows that the emotion recognition during hand-object interactions is possible and it may foster development of new intelligent user interfaces
Young Social Entrepreneurs and Social Challenges: The “Parallelo” Case Study
No full textThe chapter is focused on social entrepreneurship and, after providing a comprehensive literature review on the topics, aims at providing evidence of the decision-making process of social entrepreneurs and of the strategies they implement by focusing on a single case study, namely “Parallelo.” Parallelo was founded in 2017 by four young
Italian social entrepreneurs with the aim of promoting social inclusion of fragile categories and foreign people. Their “formula” is the “social lab” involving creative craftsmen that collaborate in the design and creation of sustainable products based on recyclable/discarded materials. By implementing a narrative approach, the case study is developed following step by step the social enterprise establishment and development. In doing so, the study aims at contributing to the social entrepreneurship field of research and at providing insights for practitioners about how decisions are made and strategies implemented within social entrepreneurial teams
The role of object motion in visuo-haptic exploration during development
No full textSince infancy we explore novel objects to infer their shape. However, how exploration strategies are planned to combine different sensory inputs is still an open question. In this work we focus on the development of visuo-haptic exploration strategies, by analyzing how school-aged children explore iCube, a sensorized cube measuring its orientation in space and contacts location. Participants' task was to find specific cube faces while they could either only touch the static cube (tactile), move and touch it (haptic) or move, touch and look at it (visuo-haptic). Visuo-haptic performances were adult-like at 7 years of age, whereas haptic exploration was not as effective until 9 years. Moreover, the possibility to rotate the object represented a difficulty rather than an advantage for the youngest age group. These findings are discussed in relation to the development of visuo-haptic integration and in the perspective of enabling early anomalies detection in explorative behaviors
A Self for robots: core elements and ascription by humans
No full textModern robotics is interested in developing humanoid robots with meta-cognitive capabilities in order to create systems that have the possibility of dealing efficiently with the presence of novel situations and unforeseen inputs. Given the relational nature of human beings, with a glimpse into the future of assistive robots, it seems relevant to start thinking about the nature of the interaction with such robots, increasingly human-like not only from the outside but also in terms of behavior. The question posed in this abstract concerns the possibility of ascribing the robot not only a mind but a more profound dimension: a Self
Using Robot Adaptivity to Support Learning in Child-Robot Interaction
No full textPrevious research has shown that if a robot invests physical effort in teaching human partners a new skill, the teaching will be more effective and the partners will reciprocate by investing more effort and patience when their turn to teach comes. In the current study, we extend this research to child-robot interaction. To this end, we devised a scenario in which a humanoid robot (iCub) and a child participant alternated in teaching each other new skills. In the robot teaching phase iCub taught participants sequences of movements, which they had to memorize and repeat. The robot then repeated the demonstration a second time: in the high effort (or Adaptive) condition, the iCub slowed down its movements when repeating the demonstration whereas in the low effort (or Unadaptive) condition he sped the movements up. In the participant teaching phase, children were asked to give the robot a demonstration of three symbols, and then to repeat it if the robot had not understood. The results reveal that children learned the sequences more effectively when the iCub adapted its movements to the learner, and that, when their turn to teach to the robot came, they slowed down and increased segmentation when repeating the demonstration
A user-centred framework for explainable artificial intelligence in human-robot interaction
No full textModeling Human Motion: A Task at the Crossroads of Neuroscience, Computer Vision and Robotics
No full textHuman motion understanding has been studied for decades but yet it remains a challenging research field which attracts the interest from different disciplines. This book wants to provide a comprehensive view on this topic, closing the loop between perception and action, starting from humans’ action perception skills and then moving to computational models of motion perception and control adopted in robotics. To achieve this aim, the book collects contributions from experts in different fields, spanning neuroscience, computer vision and robotics. The first part focuses on the features of human motion perception and its neural underpinnings. The second part considers motion perception from the computational perspective, providing a view on cutting-edge machine learning solutions. Finally, the third part takes into account the implications for robotics, exploring how motion and gestures should be generated by communicative artificial agents to establish intuitive and effective human-robot interaction
A Cognitive Architecture for Socially Adaptable Robots
No full textA social robot that's aware of our needs and continuously adapts its behaviour to them has the potential of creating a complex, personalized, human-like interaction of the kind we are used to have with our peers in our everyday lives. However adaptability, being a result of a process of learning and making errors, brings with itself also uncertainty, and we as humans are heavily relying on the machines we use to always be predictable and consistent. To further explore this, we propose a cognitive architecture for the humanoid robot iCub supporting adaptability and we attempt to validate its functionality and establish the potential benefits it could bring with respect to the more traditional pre-scripted interaction protocols for robots
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