Endovascular Robot

Endovascular robots are being developed to improve the safety and precision of minimally invasive vascular procedures. Current research focuses on achieving autonomous navigation, often employing reinforcement learning algorithms and advanced path planning methods like BDA-star, guided by real-time image processing of fluoroscopic data. Key challenges addressed include providing reliable haptic feedback to surgeons during training and operations, and developing open-source simulators like CathSim to accelerate algorithm development and testing. These advancements hold significant promise for reducing human error, improving surgical outcomes, and expanding access to complex endovascular interventions.