The millimeter wave (mmWave) bands have attracted considerable attention for high precision localization applications due to the ability to capture high angular and temporal resolution measurements. This project explores mmWave-based positioning for a target localization problem where a fixed target broadcasts mmWave signals and a mobile robotic agent attempts to capture the signals to locate and navigate to the target. The project includes:

• Development of AI-based methods for navigation
• Integration with state-of-the-art neural SLAM methods with camera day
• Simulation tools and data sets developed with detailed 3D models and ray tracing
• Exploration of deep re-inforcement learning techniques for improved navigation

 


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