Revolutionizing Human-Robot Interaction (HRI): Multimodal Intelligent Robotic System for Responsive Collaboration
Keywords:
multimodal, human-robot interaction, robotics, communication, sensors, multi-modal inputsAbstract
With the advancement of robotics throughout time, human-robot interaction (HRI) is now crucial for providing optimal user experience, reducing tedious activities, and increasing public acceptance of robots. A central aspect of the investigation involves developing context-aware robotic systems that can dynamically adapt to varying environmental conditions and user contexts. By incorporating real-time adaptability into the robotic framework, the research aims to create a more responsive and intuitive human-robot collaboration experience. In order to facilitate the advancement of robots, it is imperative to adopt innovative Human-Robot Interaction (HRI) strategies, with a particular emphasis on fostering a more natural and adaptable mode of interaction. Multimodal HRI, as a recently emerging methodology, provides a means for individuals to engage with robots through diverse modalities, encompassing voice, images, text, eye movement, touch, and even bio-signals such as EEG and ECG. This approach marks a significant shift in HRI paradigms, offering a versatile framework for enhanced communication between humans and robots. In this paper, a Multi-Modal Intelligent Robotic System (MIRS) is proposed, comprising several distinct modules. Leveraging various sensors such as image, sound, and depth, these modules can operate independently or collaboratively to facilitate efficient interaction between humans and robots. Three key components are identified and implemented in this research, which includes the location and posture of the object, information extraction, gesture analysis and eye tracking. Experimental evaluations were conducted to gauge the performance of these interaction interfaces, and the findings underscored the effectiveness of the proposed approach.
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