Tag: sensor fusion
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Generative AI-Enhanced Sensor Fusion: Robust LiDAR-Radar Inpainting and Restoration in Extreme Weather
Introduction This thesis investigates the application of Generative AI for the intelligent fusion of heterogeneous sensor data. The goal is to develop a Generative AI framework, specifically leveraging Conditional Diffusion Models, for real-time point cloud restoration. The research focuses on using Radar data, which is inherently weather-resilient, as a “semantic and physical prior” to denoise
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Resilient Autonomous Navigation via Generative AI: Virtual Sensor Synthesis for Real-Time Fault Recovery
Introduction What happens when an autonomous vehicle’s camera is covered by mud or a LiDAR module suffers a hardware failure? Currently, the car performs a “safe stop.” This thesis aims to replace this passive safety with Generative AI-driven resilience, creating a system that can “imagine” missing data. Goals The project focuses on building a Virtual