1 citations · 2 across the 8 of their papers we have counts for
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ELLIPSE: Evidential Learning for Robust Waypoints and Uncertainties
Zihao Dong, Chanyoung Chung, Dong-Ki Kim +5
Robust waypoint prediction is crucial for mobile robots operating in open-world, safety-critical settings. While Imitation Learning (IL) methods have demonstrated great success in…
VENTURA: Adapting Image Diffusion Models for Unified Task Conditioned Navigation
Arthur Zhang, Xiangyun Meng, Luca Calliari +5
Robots must adapt to diverse human instructions and operate safely in unstructured, open-world environments. Recent Vision-Language models (VLMs) offer strong priors for grounding…
Enter the Mind Palace: Reasoning and Planning for Long-term Active Embodied Question Answering
Muhammad Fadhil Ginting, Dong-Ki Kim, Xiangyun Meng +10
As robots become increasingly capable of operating over extended periods -- spanning days, weeks, and even months -- they are expected to accumulate knowledge of their environments…
TerrainNet: Visual Modeling of Complex Terrain for High-speed, Off-road Navigation
Xiangyun Meng, Nathan Hatch, Alexander Lambert +11
Effective use of camera-based vision systems is essential for robust performance in autonomous off-road driving, particularly in the high-speed regime. Despite success in structure…
Deep Forward and Inverse Perceptual Models for Tracking and Prediction
Alexander Lambert, Amirreza Shaban, Amit Raj +2
We consider the problems of learning forward models that map state to high-dimensional images and inverse models that map high-dimensional images to state in robotics. Specifically…