Abstract
The Simultaneous Localization and Mapping (SLAM) method is widely used in the positioning and mapping of robots. In the medical field, SLAM is used in auxiliary medical robots and surgical robots. In endoscopic surgery, SLAM performs endoscopic positioning and scene graph construction for the surgical environment based on the information collected by the endoscope. For research on endoscopic SLAM, this article will first introduce the application of SLAM in endoscopic surgery in recent years. This paper summarizes the innovations and future work of relevant literature in recent years and identifies existing problems in SLAM in endoscopic surgery. Next, this article will introduce the combination of deep learning and SLAM in endoscopic surgery and list some specific applications. Finally, this paper will give a prospect for the future application of SLAM in endoscopic surgery. The research in this paper will be of great value to applying SLAM in endoscopic surgery and conducive to the development of future endoscopic SLAM.
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