1 citations · 1 across the 12 of their papers we have counts for
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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…
Factored Diffusion Policies:Compositionally Generalized Robot Control with a Single Score Network
Sayan Mitra, Ege Yuceel, Noah Giles +1
Robotic tasks are typically specified by a tuple of factors, such as the object to be grasped, the obstacles to be avoided, the color of the target, and so on. Collecting expert de…
Minimal Information Control Invariance via Vector Quantization
Ege Yuceel, Teodor Tchalakov, Sayan Mitra
Safety-critical autonomous systems must satisfy hard state constraints under tight computational and sensing budgets, yet learning-based controllers are often far more complex than…
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…