How can social robot use cases in healthcare be pushed - with an interoperable programming interface

Area of Science:

• Robotics
• Human-Computer Interaction
• Software Engineering

Background:

• Current robot middleware is often complex or outdated, hindering usability for non-experts.
• There is a need for user-friendly middleware that integrates with existing robot platforms.

Purpose of the Study:

• To develop a new, user-friendly robot middleware based on Android.
• To facilitate robot control for non-experts by simplifying interaction with existing robot SDKs and middleware.

Main Methods:

• Developed an Android application for the Cruzr robot's tablet, featuring a WebSocket server for control via Python or other compatible languages.
• Integrated Google Cloud Voice services for text-to-speech and speech-to-text functionalities.
• Created a web interface for direct robot control and implemented various robot functions including navigation and barcode scanning.

Main Results:

• Successfully deployed the middleware on a Cruzr robot, demonstrating control via WebSocket API and Python.
• Showcased adaptability by porting the interface to a Pepper robot, with potential for broader platform compatibility.
• Implemented healthcare use cases with positive user feedback, highlighting the middleware's practical application.

Conclusions:

• The developed middleware offers a simplified approach to robot control, suitable for non-experts.
• The system's architecture supports adaptability to different robots and platforms, facilitating broader research and educational applications.
• Future work includes simplifying programming with natural text-to-code generators and further exploration of human-robot interaction.