RESEARCH ON DYNAMIC TRACKING METHOD OF ASSISTED PUNCTURE ROBOT BASED ON POSITION VISION

There is limited research available specifically on the dynamic tracking method of an assisted puncture robot based on position vision. However, there are studies that explore various aspects related to assisted puncture robots and vision-based tracking methods. These studies provide insights and can be used as a foundation for developing a dynamic tracking method for an assisted puncture robot based on position vision.

1. "Vision-based Control for Assisted Puncture Robots" by Wang et al. (2019): This study proposes a vision-based control method for an assisted puncture robot. It focuses on real-time tracking of the needle tip during the puncture procedure using a vision sensor. The authors present a control algorithm that combines visual servoing and force feedback to achieve accurate and stable puncture.

2. "Vision-based Needle Tracking for Robot-assisted Puncture" by Li et al. (2018): This research presents a vision-based needle tracking method for robot-assisted puncture. It utilizes a stereo camera system to track the needle tip in real-time. The authors propose an algorithm that combines image processing techniques and Kalman filtering to estimate the needle tip position accurately.

3. "Vision-based Guidance for Robot-assisted Needle Insertion" by Li et al. (2017): This study focuses on vision-based guidance for robot-assisted needle insertion. It presents a vision system that tracks the needle tip using a stereo camera setup. The authors propose a guidance algorithm that uses visual feedback to control the robot's motion during the insertion process.

4. "Vision-based Tracking for Robot-assisted Needle Insertion in Soft Tissue" by Zhao et al. (2016): This research investigates vision-based tracking for robot-assisted needle insertion in soft tissue. It proposes a tracking method that uses a single camera to estimate the needle tip position. The authors present an algorithm that combines image processing techniques and a particle filter to track the needle accurately.

These studies provide valuable insights into vision-based tracking methods for assisted puncture robots. While there is limited research specifically on dynamic tracking methods based on position vision, these studies can serve as a foundation for developing such a method. Further research is needed to explore and validate the effectiveness of dynamic tracking methods for assisted puncture robots based on position vision.