Augmented Reality-Centered Position Navigation for Wearable Devices with Machine Learning Techniques

Area of Science:

• Computer Science
• Human-Computer Interaction
• Robotics

Background:

• Traditional navigation tools have evolved from maps to GPS-enabled smartphones.
• While outdoor navigation is precise, indoor navigation systems struggle with accuracy.
• Existing indoor navigation technologies include Bluetooth, Wi-Fi, RFID, and computer vision.

Purpose of the Study:

• To identify the limitations of current indoor navigation solutions.
• To propose an alternative indoor navigation approach utilizing augmented reality (AR) and ARCore.
• To enhance the precision and user experience of indoor wayfinding.

Main Methods:

• Review of existing indoor navigation technologies and their shortcomings.
• Development of a novel indoor navigation system leveraging augmented reality (AR).
• Integration of ARCore to enable AR experiences on smartphones and tablets for navigation.

Main Results:

• Identified significant precision issues with current indoor navigation methods.
• Demonstrated the potential of ARCore to improve indoor navigation accuracy.
• Showcased how AR can provide a more intuitive and precise indoor wayfinding experience.

Conclusions:

• Augmented reality (AR) and ARCore offer a promising alternative to current indoor navigation systems.
• Smartphone-based AR navigation can overcome the precision limitations of existing technologies.
• Further development in AR technology can revolutionize indoor navigation.