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Semantic Coupling Framework for Autonomous Laparoscopic Control
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Enduo Zhao and other authors propose a closed-loop autonomous laparoscopic control framework that couples real-time surgical phase recognition with visual perception for camera motion compensation, leveraging phase dependencies among surgical entities to improve target state estimation under occlusion and entity overlap. The authors evaluated surgical phase recognition and target tracking on benchmark datasets; phantom experiments showed that compared with fixed-field-of-view control, target visibility and task execution performance improved under this framework. The paper has been submitted to IEEE Robotics and Automation Letters (RA-L).
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- Semantic-Coupled Perception Framework for Autonomous Laparoscope Control
This paper proposes a closed-loop autonomous laparoscope control framework that couples real-time surgical phase recognition with camera-motion-compensated visual perception, using phase dependencies among surgical entities to improve target state estimation under occlusion and entity overlap. Surgical phase recognition and target tracking were evaluated on benchmark datasets, and phantom experiments showed improved target visibility and task execution performance compared with fixed-field-of-view control. The paper was submitted to IEEE Robotics and Automation Letters (RA-L).
arXiv cs.RO ·