1 citations · 2 across the 6 of their papers we have counts for
7 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…
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…
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…
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,…
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…
ObVi-SLAM: Long-Term Object-Visual SLAM
Amanda Adkins, Taijing Chen, Joydeep Biswas
Robots responsible for tasks over long time scales must be able to localize consistently and scalably amid geometric, viewpoint, and appearance changes. Existing visual SLAM approa…
Probabilistic Object Maps for Long-Term Robot Localization
Amanda Adkins, Taijing Chen, Joydeep Biswas
Robots deployed in settings such as warehouses and parking lots must cope with frequent and substantial changes when localizing in their environments. While many previous localizat…