The vocabulary problem in human-system communication
Communications of the ACM
IEEE Intelligent Systems
The human-robot interaction operating system
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
A computational model of multi-modal grounding for human robot interaction
SigDIAL '06 Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue
Human-robot interaction in rescue robotics
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Mixed-initiative in human augmented mapping
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Can i help you?: a spatial attention system for a receptionist robot
ICSR'10 Proceedings of the Second international conference on Social robotics
Talking with robots about objects: a system-level evaluation in HRI
HRI '12 Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction
A cognitive approach for robots' autonomous learning
IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advances in computational intelligence - Volume Part I
Robotics and Autonomous Systems
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If robots are to succeed in novel tasks, they must be able to learn from humans. To improve such human-robot interaction, a system is presented that provides dialog structure and engages the human in an exploratory teaching scenario. Thereby, we specifically target untrained users, who are supported by mixed-initiative interaction using verbal and non-verbal modalities. We present the principles of dialog structuring based on an object learning and manipulation scenario. System development is following an interactive evaluation approach and we will present both an extensible, event-based interaction architecture to realize mixed-initiative and evaluation results based on a video-study of the system. We show that users benefit from the provided dialog structure to result in predictable and successful human-robot interaction.