Intention through interaction: toward mutual intention in real world interactions
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Learning and interacting in human-robot domains
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A Cross-Platform Robotic Architecture for Autonomous Interactive Robots
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Artifact-mediated society and social intelligence design
Artificial intelligence
Using physiological signals to detect natural interactive behavior
Applied Intelligence
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A prerequisite of any successful social robot is the ability to express its internal state and intention to humans in a natural way. Many researchers studied verbal and nonverbal feedback from humanoid robots or humanoid robotic heads but there is little research about the possible feedback mechanisms of non-humanoid and especially miniature robots. The TalkBack experiment is a trial to fill this gap by investigating the effectiveness of using motion cues as a feedback mechanism and comparing it to verbal feedback. The results of the experiment showed that there is no significant difference in the task completion accuracy and time or in the feeling of naturalness between these two modalities and there is a statistically significant improvement when using any of them compared with the no-feedback case. Moreover the subjects selected the motion cues feedback mechanism more frequently as the preferred feed-back modality for them.