Anthropomorphic Human-Robot Interaction Framework: Attention Based Approach - Archive ouverte HAL
Communication Dans Un Congrès Année : 2024

Anthropomorphic Human-Robot Interaction Framework: Attention Based Approach

Résumé

Robots need to identify environmental cues like humans do for effective human-robot interaction (HRI). Human attention models simulate the way humans process visual information, making them useful for identifying important regions in images/videos. In this paper, we explore the use of human attention models in developing intuitive and anthropomorphic HRI. Our approach combines a saliency model and a moving object detection model. The framework is implemented using the ROS framework on Pepper, a humanoid robot. To evaluate the effectiveness of our system, we conducted both subjective and qualitative measures, including subjective rating measures to evaluate intuitiveness, trust, engagement, and user satisfaction, and quantitative measures of our human attention subsystem against state-of-the-art models. Our extensive experiments demonstrate the significant impact of our framework in enabling intuitive and anthropomorphic human-robot interaction.
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Dates et versions

hal-04585013 , version 1 (23-05-2024)

Identifiants

Citer

Natnael Wondimu, Maëlic Neau, Antoine Dizet, Ubbo Visser, Cédric Buche. Anthropomorphic Human-Robot Interaction Framework: Attention Based Approach. Robot World Cup 2023, Jul 2023, Bordeaux, France. pp.262-274, ⟨10.1007/978-3-031-55015-7_22⟩. ⟨hal-04585013⟩
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