<p>The umbilical, a key component in offshore energy extraction, plays a vital role in ensuring the stable operation of the entire production system. The extensive variety of cross-sectional components creates highly complex layout combinations. Furthermore, due to constraints in component quantity and geometry within the cross-sectional layout, filler bodies must be incorporated to maintain cross-section performance. Conventional design approaches based on manual experience suffer from inefficiency, high variability, and difficulties in quantification. This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations. Initially, the research establishes a multi-objective optimization model that considers compactness, balance, and wear resistance of the cross-section, employing an enhanced genetic algorithm to achieve a near-optimal layout. Subsequently, the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps. To manage the variability and diversity of these vacant regions, the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions, overcoming the constraints of uniform-size fillers. Additionally, the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers, enabling layer-by-layer optimization and filling. This approach reduces manufacturing equipment requirements while ensuring practical production process feasibility. The methodology is validated through a specific umbilical case study. The results demonstrate improvements in compactness, balance, and wear resistance compared with the initial cross-section, offering novel insights and valuable references for filler design in umbilical cross-sections.</p>