An Experiment of Cone-Sleeve Recognition in UAV Aerial Refueling Using Multi-Modal ViT Technology
Abstract
This study presents a Semantically-Decoupled Vision Transformer (SD-ViT)framework for robust aerial refueling drogue acquisition. To resolve the conflict between high-latency Transformers and real-time constraints, we introduce an “Offline-Prompt, Online-Vision” architecture integrated with hardware-aware tensor optimization. Flight tests under severe backlighting show that SD-ViT outperforms traditional color segmentation and provides stronger robustness under domain shift than a YOLOv8 baseline. With inference optimization, the proposed method mitigates computational bottlenecks, offering improved feasibility for onboard applications.
Fields of Study & Subjects
Advanced Neural Network Applications
Aerospace Engineering and Control Systems
Robot Manipulation and Learning
Publication details
- Journal / source
- Guidance Navigation and Control
- Volume
- 06
- Issue
- 02
- Pages
- 247–250
- Publication date
- 13 February 2026
- Language
- EN