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Correcting Learning-based Perception for Safety
Yan Miao, Hussein Darir, Sayan Mitra
Learning-enabled perception is important in many autonomous systems. Unlike traditional sensors, the boundary where ML perception does or does not work is poorly characterized. Inc…
FalconTrack: Photorealistic Auto-Labeled Perception and Physics-Aware Vision-Based Aerial Tracking
Yan Miao, Karteek Gandiboyina, Noah Giles +4
Vision-based aerial tracking is critical in GPS-denied environments. Reliable perception for tracking depends on large-scale labeled data, yet most photorealistic datasets rely on…
Task-Aware Environment Augmentation for Reliable Navigation via Shielded Conditional Diffusion
Bharawee Phoompho, Gokul Puthumanaillam, Yan Miao +4
Reliable trajectory planning under partial observability depends not only on computing a feasible geometric path, but also on whether the robot receives informative observations wh…
FalconApp: Rapid iPhone Deployment of End-to-End Perception via Automatically Labeled Synthetic Data
Yan Miao, Will Shen, Sayan Mitra
Reliable perception for robotics depends on large-scale labeled data, yet real-world datasets rely on heavy manual annotation and are time-consuming to produce. We present FalconAp…