3 papers
cs.CV2026
GDA-YOLO11: Amodal Instance Segmentation for Occlusion-Robust Robotic Fruit Harvesting
Caner Beldek, Emre Sariyildiz, Son Lam Phung +1
Occlusion remains a critical challenge in robotic fruit harvesting, as undetected or inaccurately localised fruits often results in substantial crop losses. To mitigate this issue,…
cs.RO2025
Multi-vision-based Picking Point Localisation of Target Fruit for Harvesting Robots
C. Beldek, A. Dunn, J. Cunningham +3
This paper presents multi-vision-based localisation strategies for harvesting robots. Identifying picking points accurately is essential for robotic harvesting because insecure gra…
cs.RO2025
Sensing-based Robustness Challenges in Agricultural Robotic Harvesting
C. Beldek, J. Cunningham, M. Aydin +3
This paper presents the challenges agricultural robotic harvesters face in detecting and localising fruits under various environmental disturbances. In controlled laboratory settin…