Autonomous navigation in agricultural environments has emerged as a key innovation in modern agritech, providing significant benefits in terms of efficiency, cost reduction, and sustainability. In particular, autonomous systems in vineyards can alleviate labor shortages, optimize resource usage, and enable precision agriculture practices. However, the structured yet highly variable nature of vineyards presents unique challenges for autonomous navigation. Vineyards are characterized by narrow and uneven pathways, curved and sloped terrains, and dense vegetation that can obstruct visibility and interfere with traditional localization methods. Furthermore, environmental factors such as changing lighting conditions, seasonal variations, and occlusions from foliage add additional layers of complexity to perception and decision-making systems.