1,213 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
Eye tracking for human robot interaction
No full textHumans use eye gaze in their daily interaction with other humans. Humanoid robots, on the other hand, have not yet taken full advantage of this form of implicit communication. We designed a passive monocular gaze tracking system implemented on the iCub humanoid robot [Metta et al. 2008]. The validation of the system proved that it is a viable low-cost, calibration-free gaze tracking solution for humanoid platforms, with a mean absolute error of about 5 degrees on horizontal angle estimates. We also demonstrated the applicability of our system to human-robot collaborative tasks, showing that the eye gaze reading ability can enable successful implicit communication between humans and the robot
Towards better eye tracking in human robot interaction using an affordable active vision system
No full textEye gaze tracking for a humanoid robot
No full textHumans use eye gaze in their daily interaction with other humans. Humanoid robots, on the other hand, have not yet taken full advantage of this form of implicit communication. In this paper we present a passive monocular gaze tracking system implemented on the iCub humanoid robot. The validation of the system proved that it is a viable low-cost, calibration-free gaze tracking solution for humanoid platforms, with a mean absolute error of about 5 degrees on horizontal angle estimates. We also demonstrated the applicability of our system to human-robot collaborative tasks, showing that the eye gaze reading ability can enable successful implicit communication between humans and the robot. Finally, in the conclusion we give generic guidelines on how to improve our system and discuss some potential applications of gaze estimation for humanoid robots
Robot reading human gaze: Why eye tracking is better than head tracking for human-robot collaboration
No full textRobots are at the position to become our everyday companions in the near future. Still, many hurdles need to be cleared to achieve this goal. One of them is the fact that robots are still not able to perceive some important communication cues naturally used by humans, e.g. gaze. In the recent past, eye gaze in robot perception was substituted by its proxy, head orientation. Such an approach is still adopted in many applications today. In this paper we introduce performance improvements to an eye tracking system we previously developed and use it to explore if this approximation is appropriate. More precisely, we compare the impact of the use of eye- or head-based gaze estimation in a human robot interaction experiment with the iCub robot and naïve subjects. We find that the possibility to exploit the richer information carried by eye gaze has a significant impact on the interaction. As a result, our eye tracking system allows for a more efficient human-robot collaboration than a comparable head tracking approach, according to both quantitative measures and subjective evaluation by the human participants
If looks could kill: Humanoid robots play a gaze-based social game with humans
No full textGaze plays an important role in everyday communication between humans. Eyes are not only used to perceive information during interaction, but also to control it. Humanoid robots on the other hand are not yet very proficient in understanding and using gaze. In our study we enabled two humanoid robots to perceive and exert gaze actions. We then performed a pilot experiment with the two android robots playing the 'Wink Murder' game with human players. We demonstrate that the designed framework allows the robots to complete the game successfully, validating the efficacy of our gaze tracking system. Moreover, human participants exhibited a rich variety of natural behaviors in the game, suggesting that it could represent a valid scenario for a more in-depth investigation of human-humanoid interaction
Tactile Sensing Improves Handshake between Humans and Robots
No full textShaking hands as a gesture of greeting is a common social practice observed in numerous cultures. This behavior is acquired during the early years of childhood. We constructed a humanoid robot with the objective of greeting children and their parents at a hospital. During the robot’s initial deployment, children frequently extended their hands to grasp the robot’s hand in order to initiate a handshake. Nevertheless, social robots, including our own, require preparation for such activities. To address this challenge, we implemented an interactive handshaking protocol for our robot, which employs tactile sensors embedded in the right hand to adapt and detect the optimal timing for each phase of the handshake. In a user study, the adaptive handshake was compared with two other protocols, one with constant timing and the second with passive, compliant control, which expected the users to lead the activity. The results of statistical tests revealed that the participants expressed a preference for the adaptive robot, perceiving its behavior as more natural, pleasant, and reactive. In conclusion, it was found that the implementation of handshaking procedures on social robots with arms can facilitate more natural interaction and deepen trust. Furthermore, insights are provided regarding prospective enhancements to the platform, including integrating neuromorphic sensing technologies for sensorimotor tactile control.</p
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