ABSTRACT
This study focuses on a robot vision localization method for coping with the operational task of automatic nasal swab sampling. The application is important in the detection and epidemic prevention of Corona Virus Disease 2019 (COVID-19) to alleviate the large-scale negative impact of individuals suffering from pneumonia owing to COVID-19. In this method, the idea of a hierarchical decision network is used to consider the strong infectious characteristics of the COVID-19, which is followed by processing the robot behavior constraint condition. The visual navigation and positioning method using a single-arm robot for sampling is also planned, which considers the operation characteristics of medical staff. In the decision network, the risk factor for potential contact infection caused by swab sampling operations is established to avoid the spread among personnel. A robot visual servo control with artificial intelligence characteristics is developed to achieve a stable and safe nasal swab sampling operation. Experiments demonstrate that the proposed method can achieve good vision positioning for the robots and provide technical support for managing new major public health situations.
ABSTRACT
The purpose of this paper is to develop an autonomous tracking algorithm based on adaptive fusion kinematics method, the autonomous laparoscope control algorithm and adaptive fusion kinematics method are proposed for semi-autonomous surgery, focus on solving the problems of autonomous laparoscope field of view control for surgical robot system. A novel autonomous tracking algorithm is proposed. To realize more robust tracking, an adaptive fusion kinematics method based on fuzzy logic is proposed, the method adaptive associates the kinematics information of surgical robot system and the laparoscope information. The proposed methods are implemented on the laparoscopic minimally invasive surgical robot system which is developed by our laboratory. Two experiments are carried out, the results indicate that the accurate autonomous field of view control is achieved with the addition of laparoscope information, laparoscopic motion frequency is reduced, the methods can avoid the laparoscope continuous motion and ensure the stability of field of view. The proposed methods improve the intelligence level of surgical robot system.
