Design of an Autonomous Delivery System for Vascular Intervention Robots Based on Curvature Variation

With the rising incidence of cardiovascular and cerebrovascular diseases, vascular interventional surgery has become a primary treatment for conditions such as stroke, vascular occlusion, and aneurysms. However, the need for physicians to wear heavy lead aprons and endure prolonged radiation exposure, combined with the high technical demands of the procedure, has led to a declining number of willing practitioners. To address these challenges, vascular interventional surgery robots have emerged, offering effective radiation isolation and improved procedural standardization and precision. Nevertheless, due to the need for remote operation, current robotic systems lack real-time environmental perception, resulting in a loss of embodied intelligence and increased procedural risk. To alleviate the operational burden on doctors and enhance robotic intelligence while reducing dependence on frequent angiographic imaging, this study proposed an autonomous guidewire delivery system based on the curvature variation of interventional instruments. Experimental results demonstrated that the system can effectively detect collisions between the instrument and vessel wall, and promptly halt advancement upon risk identification, thereby improving autonomous safety and clinical adaptability.