Huang H.-EYen S.-YChu C.-FSuk F.-MLien G.-SCHIH-WEN LIU2022-04-252022-04-25202120452322https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112688726&doi=10.1038%2fs41598-021-95760-7&partnerID=40&md5=a19b7d1d76d6df09c41022b083eb2848https://scholars.lib.ntu.edu.tw/handle/123456789/607022This paper presents an autonomous navigation system for cost-effective magnetic-assisted colonoscopy, employing force-based sensors, an actuator, a proportional–integrator controller and a real-time heuristic searching method. The force sensing system uses load cells installed between the robotic arm and external permanent magnets to derive attractive force data as the basis for real-time surgical safety monitoring and tracking information to navigate the disposable magnetic colonoscope. The average tracking accuracy on magnetic field navigator (MFN) platform in x-axis and y-axis are 1.14 ± 0.59?mm and 1.61 ± 0.45?mm, respectively, presented in mean error ± standard deviation. The average detectable radius of the tracking system is 15?cm. Three simulations of path planning algorithms are presented and the learning real-time A* (LRTA*) algorithm with our proposed directional heuristic evaluation design has the best performance. It takes 75 steps to complete the traveling in unknown synthetic colon map. By integrating the force-based sensing technology and LRTA* path planning algorithm, the average time required to complete autonomous navigation of a highly realistic colonoscopy training model on the MFN platform is 15?min 38?s and the intubation rate is 83.33%. All autonomous navigation experiments are completed without intervention by the operator. ? 2021, The Author(s).[SDGs]SDG3journal article10.1038/s41598-021-95760-7343897602-s2.0-85112688726