Human Interaction Smart Subsystem-Extending Speech-Based Human-Robot Interaction Systems with an Implementation of...

Area of Science:

• Robotics
• Human-Computer Interaction
• Artificial Intelligence

Background:

• Current Human-Robot Interaction (HRI) systems often lack comprehensive pre-interaction data acquisition.
• Integrating external subsystems can significantly enhance the intelligence and adaptability of robotic systems.

Purpose of the Study:

• To present a detailed HRI systems architecture focused on advanced information acquisition.
• To introduce and evaluate custom Internet-of-Things (IoT)-based sensor subsystems for interlocutor identification and parameter acquisition.
• To demonstrate the benefits of integrating these subsystems into an AI interaction framework.

Main Methods:

• Development and implementation of IoT-based sensor subsystems connected to Smart Infrastructure.
• Extension of an AI interaction framework with device-based human identification, visual identification, and audio-based localization subsystems.
• Detailed analysis and prototype implementation of a Bluetooth Human Identification Smart Subsystem within a real-world office environment.

Main Results:

• The proposed architecture enables robust interlocutor identification and acquisition of initial interaction parameters before interaction begins.
• Integration of external subsystems (e.g., Bluetooth Human Identification) enhances the robotic system's knowledge base and interaction capabilities.
• A functional prototype demonstrated the feasibility and benefits of the integrated Smart Infrastructure and HRI system.

Conclusions:

• The novel HRI architecture significantly improves interaction by leveraging pre-interaction data.
• IoT and Smart Infrastructure integration offers a powerful approach to creating more informed and responsive robotic systems.
• The evaluated subsystems provide a scalable and effective method for enhancing HRI.