• Laser & Optoelectronics Progress
  • Vol. 61, Issue 18, 1815003 (2024)
Kefu Song1,2, Rui Tang1, Feifei Guo3, Zexin Shen1..., Huixiong Zeng1 and Jun Li1,3,*|Show fewer author(s)
Author Affiliations
  • 1Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350117, Fujian, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Quanzhou Vocational and Technical University, Quanzhou 362000, Fujian, China
  • show less
    DOI: 10.3788/LOP232708 Cite this Article Set citation alerts
    Kefu Song, Rui Tang, Feifei Guo, Zexin Shen, Huixiong Zeng, Jun Li. Surgical Robotic Arm Guidance System Based on Point Laser Precise Navigation[J]. Laser & Optoelectronics Progress, 2024, 61(18): 1815003 Copy Citation Text show less

    Abstract

    Automated surgical guidance systems are increasingly important in clinical settings, driven by advancements in image detection technologies and the growing demand for surgical procedures. However, the need for the system to have real-time visual precision guidance restricts the range of applications in clinical surgery. When a visual signal guides the robotic arm for path planning, the inefficiency of traditional algorithms in low planning can hinder the real-time capability of the system. To address these problems, a navigation control system based on a point-laser-guided surgical robotic arm is proposed. The visual part is based on the YOLOv5 network and preprocessed using the super-resolution reconstruction algorithm. Fusion feature aggregation and single-scale recognition improvement strategies are proposed to achieve rapid and accurate point-laser tracking. For motion planning, a rapidly-exploring random tree (RRT) algorithm that integrates target bias and bidirectional expansion is proposed to constrain the target point attitude using lesion point cloud information for collision pre-detection and planning decision during path generation. The validity and feasibility of the proposed algorithm were verified through experiments, demonstrating that the optimized algorithm achieves an AP50 recognition accuracy of 97.6% and an AP75 recognition accuracy of 83.5%. Moreover, the improved RRT algorithm accurately and rapidly plans the optimal obstacle avoidance path, achieving a 7.2 percentage points improvement over YOLOv5 in traditional video target recognition.
    Kefu Song, Rui Tang, Feifei Guo, Zexin Shen, Huixiong Zeng, Jun Li. Surgical Robotic Arm Guidance System Based on Point Laser Precise Navigation[J]. Laser & Optoelectronics Progress, 2024, 61(18): 1815003
    Download Citation