142 citations · 712 across the 76 of their papers we have counts for
9 papers · 1 filter
Generating Out-Of-Distribution Scenarios Using Language Models
Erfan Aasi, Phat Nguyen, Shiva Sreeram +3
The deployment of autonomous vehicles controlled by machine learning techniques requires extensive testing in diverse real-world environments, robust handling of edge cases and out…
Learning autonomous driving from aerial imagery
Varun Murali, Guy Rosman, Sertac Karaman +1
In this work, we consider the problem of learning end to end perception to control for ground vehicles solely from aerial imagery. Photogrammetric simulators allow the synthesis of…
DecTrain: Deciding When to Train a Monocular Depth DNN Online
Zih-Sing Fu, Soumya Sudhakar, Sertac Karaman +1
Deep neural networks (DNNs) can deteriorate in accuracy when deployment data differs from training data. While performing online training at all timesteps can improve accuracy, it…
Joint Localization and Planning using Diffusion
L. Lao Beyer, S. Karaman
Diffusion models have been successfully applied to robotics problems such as manipulation and vehicle path planning. In this work, we explore their application to end-to-end naviga…
GEVO: Memory-Efficient Monocular Visual Odometry Using Gaussians
Dasong Gao, Peter Zhi Xuan Li, Vivienne Sze +1
Constructing a high-fidelity representation of the 3D scene using a monocular camera can enable a wide range of applications on mobile devices, such as micro-robots, smartphones, a…
Text-to-Drive: Diverse Driving Behavior Synthesis via Large Language Models
Phat Nguyen, Tsun-Hsuan Wang, Zhang-Wei Hong +2
Generating varied scenarios through simulation is crucial for training and evaluating safety-critical systems, such as autonomous vehicles. Yet, the task of modeling the trajectori…