5 papers
PreSIST: Vision-Language-Informed Object Persistence Prediction in Open-World Scenes
Amanda Adkins, Tarunvidyut Ravisankar, Joydeep Biswas
Robots deployed over long periods must reason about environments that change over time. Existing long-term perception systems often address object change reactively, updating their…
BEV-Patch-PF: Particle Filtering with BEV-Aerial Feature Matching for Off-Road Geo-Localization
Dongmyeong Lee, Jesse Quattrociocchi, Christian Ellis +5
We propose BEV-Patch-PF, a GPS-free sequential geo-localization system that integrates a particle filter with learned bird's-eye-view (BEV) and aerial feature maps. From onboard RG…
OVerSeeC: Open-Vocabulary Costmap Generation from Satellite Images and Natural Language
Rwik Rana, Jesse Quattrociocchi, Dongmyeong Lee +5
Aerial imagery provides essential global context for autonomous navigation, enabling route planning at scales inaccessible to onboard sensing. We address the problem of generating…
CLOVER: Context-aware Long-term Object Viewpoint- and Environment- Invariant Representation Learning
Dongmyeong Lee, Amanda Adkins, Joydeep Biswas
Mobile service robots can benefit from object-level understanding of their environments, including the ability to distinguish object instances and re-identify previously seen insta…
Spatiotemporal Contrastive Learning for Cross-View Video Localization in Unstructured Off-road Terrains
Zhiyun Deng, Dongmyeong Lee, Amanda Adkins +3
Robust cross-view 3-DoF localization in GPS-denied, off-road environments remains challenging due to (1) perceptual ambiguities from repetitive vegetation and unstructured terrain,…