Initiation of Interaction Detection Framework using a Nonverbal Cue for Human-Robot Interaction
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Abstract (arXiv)
This paper describes an initiation of interaction(IoI) detection framework without keywords for human-robot interaction(HRI) based on audio and vision sensor fusion in a domestic environment. In the proposed framework, the robot has its own audio and vision sensors, and can employ external vision sensor for stable human detection and tracking. When the user starts to speak while looking at the robot, the robot can localize his or her position by its sound source localization together with human tracking information. Then the robot can detect the IoI if it perceives the face of the speaker faces the robot. In case that the user does not speak directly, the robot can also detect the IoI if he or she looks at the robot for more than predefined periods of time. A state transition model for the proposed IoI detection framework is designed and verified by experiments with a mobile robot. In order to implement and associate our model in a robot architecture, all the components are implemented and integrated in the Robot Operating System(ROS) environment.
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References · 5
- 2022YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectorscited by 982
- 2017Simple Online and Realtime Tracking with a Deep Association Metriccited by 910
- 2016Simple Online and Realtime Trackingcited by 868
- 2019MediaPipe: A Framework for Building Perception Pipelinescited by 583
- 2019Multimodal Uncertainty Reduction for Intention Recognition in Human-Robot Interactioncited by 11
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