7 papers
Distilling Global Traversability Priors for Image-based Affordance Prediction in Off-road Environments
Matthew Sivaprakasam, Samuel Triest, Micah Nye +5
Standard methods for autonomous navigation in unstructured terrain are prone to myopic behaviors in long-horizon scenarios. The use of metric maps built from LiDAR or cameras provi…
AnyThermal: Towards Learning Universal Representations for Thermal Perception
Parv Maheshwari, Jay Karhade, Yogesh Chawla +8
We present AnyThermal, a thermal backbone that captures robust task-agnostic thermal features suitable for a variety of tasks such as cross-modal place recognition, thermal segment…
TartanGround: A Large-Scale Dataset for Ground Robot Perception and Navigation
Manthan Patel, Fan Yang, Yuheng Qiu +4
We present TartanGround, a large-scale, multi-modal dataset to advance the perception and autonomy of ground robots operating in diverse environments. This dataset, collected in va…
BETTY Dataset: A Multi-modal Dataset for Full-Stack Autonomy
Micah Nye, Ayoub Raji, Andrew Saba +9
We present the BETTY dataset, a large-scale, multi-modal dataset collected on several autonomous racing vehicles, targeting supervised and self-supervised state estimation, dynamic…
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation
Bowen Li, Zhaoyu Li, Qiwei Du +10
Recent years have witnessed the rapid development of Neuro-Symbolic (NeSy) AI systems, which integrate symbolic reasoning into deep neural networks. However, most of the existing b…
MAC-VO: Metrics-aware Covariance for Learning-based Stereo Visual Odometry
Yuheng Qiu, Yutian Chen, Zihao Zhang +2
We propose the MAC-VO, a novel learning-based stereo VO that leverages the learned metrics-aware matching uncertainty for dual purposes: selecting keypoint and weighing the residua…