2 papers
cs.RO2026
D-CLING: Prior-Preserving Depth-Conditioned Fine-Tuning for Navigation Foundation Models
Shintaro Nakaoka, Takayuki Kanai, Kazuhito Tanaka
Navigation Foundation Models (NFMs) trained on large cross-embodied datasets have demonstrated powerful generalizability in various scenarios. Adopting in-domain fine-tuning for an…
cs.CV2024
CLIP-Loc: Multi-modal Landmark Association for Global Localization in Object-based Maps
Shigemichi Matsuzaki, Takuma Sugino, Kazuhito Tanaka +4
This paper describes a multi-modal data association method for global localization using object-based maps and camera images. In global localization, or relocalization, using objec…