Improving backdrivability in preoperative manual manipulability of minimally invasive surgery robot

2018 ◽  
Vol 45 (1) ◽  
pp. 127-140 ◽  
Author(s):  
Shuizhong Zou ◽  
Bo Pan ◽  
Yili Fu ◽  
Shuixiang Guo
Keyword(s):  
Kalman Filter ◽  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Real Time ◽  
Invasive Surgery ◽  
Control Algorithm ◽  
Industrial Robot ◽  
Universal Method ◽  
Content Type ◽  
Robotic Arms

Purpose The purpose of this paper is to propose a control algorithm to improve the backdrivability performance of minimally invasive surgical robotic arms, so that precise manual manipulations of robotic arms can be performed in the preoperative operation. Design/methodology/approach First, the flexible-joint dynamic model of the 3-degree of freedom remote center motion (RCM) mechanisms of minimally invasive surgery (MIS) robot is derived and its dynamic parameters and friction parameters are identified. Next, the angular velocities and angular accelerations of joints are estimated in real time by the designed Kalman filter. Finally, a control algorithm based on Kalman filter is proposed to enhance the backdrivability of RCM mechanisms by compensating for the internally generated gravitational, frictional and inertial resistances experienced during the positioning and orientating. Findings The parameter identification for RCM mechanisms can be experimentally evaluated from comparison between the measured torques and the reconstructed torques. The accuracy and convergence of the real-time estimation of angular velocity and acceleration of the joint by the designed Kalman filter can be verified from corresponding simulation experiments. Manual adjustment experiments and animal experiments validate the effectiveness of the proposed backdrivability control algorithm. Research limitations/implications The backdrivability control algorithm presented in this paper is a universal method to enhance the manual operation performance of robots, which can be used not only in the medical robot preoperative manual manipulation but also in robot haptic interaction, industrial robot direct teaching and active rehabilitation training of rehabilitation robot and so on. Originality/value Compared with other backdrivability design methods, the proposed algorithm achieves good backdrivability for RCM mechanisms without using force sensors and accelerometers. In addition, this paper presents a new static friction compensation approach for a joint moving with very low velocity.

scholarly journals Real-Time Expanded Field-of-View for Minimally Invasive Surgery Using Multi-Camera Visual Simultaneous Localization and Mapping

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2106
Author(s):  
Ahmed Afifi ◽  
Chisato Takada ◽  
Yuichiro Yoshimura ◽  
Toshiya Nakaguchi
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Real Time ◽  
Invasive Surgery ◽  
Simultaneous Localization And Mapping ◽  
Field Of View ◽  
Time Dynamic ◽  
Matrix Estimation ◽  
Localization And Mapping

Minimally invasive surgery is widely used because of its tremendous benefits to the patient. However, there are some challenges that surgeons face in this type of surgery, the most important of which is the narrow field of view. Therefore, we propose an approach to expand the field of view for minimally invasive surgery to enhance surgeons’ experience. It combines multiple views in real-time to produce a dynamic expanded view. The proposed approach extends the monocular Oriented features from an accelerated segment test and Rotated Binary robust independent elementary features—Simultaneous Localization And Mapping (ORB-SLAM) to work with a multi-camera setup. The ORB-SLAM’s three parallel threads, namely tracking, mapping and loop closing, are performed for each camera and new threads are added to calculate the relative cameras’ pose and to construct the expanded view. A new algorithm for estimating the optimal inter-camera correspondence matrix from a set of corresponding 3D map points is presented. This optimal transformation is then used to produce the final view. The proposed approach was evaluated using both human models and in vivo data. The evaluation results of the proposed correspondence matrix estimation algorithm prove its ability to reduce the error and to produce an accurate transformation. The results also show that when other approaches fail, the proposed approach can produce an expanded view. In this work, a real-time dynamic field-of-view expansion approach that can work in all situations regardless of images’ overlap is proposed. It outperforms the previous approaches and can also work at 21 fps.

Real-Time 2D Surface Profile Mapping of Biological Tissue with Force Feedback in Robot-Assisted Minimally Invasive Surgery

2015 ◽  
Vol 798 ◽  
pp. 319-323
Author(s):  
Ali Reza Hassan Beiglou ◽  
Javad Dargahi
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Real Time ◽  
Invasive Surgery ◽  
Strain Gauge ◽  
Force Feedback ◽  
Surface Profile ◽  
Robot Assisted ◽  
Contact Points ◽  
Force Signal

It has been more than 20 years that robot-assisted minimally invasive surgery (RMIS) has brought remarkable accuracy and dexterity for surgeons along with the decreasing trauma for the patients. In this paper a novel method of the tissue’s surface profile mapping is proposed. The tissue surface profile plays an important role for material identification during RMIS. It is shown how by integrating the force feedback into robot controller the surface profile of the tissue can be obtained with force feedback scanning. The experiment setup includes a 5 degree of freedoms (DOFs) robot which is equipped with a strain-gauge ball caster as the force feedback. Robot joint encoders signals and the captured force signal of the strain-gauge are transferred to developed surface transformation algorithm (STA). The real-time geometrical transformation process is triggered with force signal to identify contact points between the ball caster and the artificial tissue. The 2D surface profile of tissue will be mapped based on these contact points. Real-time capability of the proposed system is evaluated experimentally for the artifical tissues in a designed test rig.

scholarly journals Development of detection method for automatic hemostasis using machine learning with abdominal cavity irrigation

2020 ◽  
Vol 7 (7) ◽  
pp. 2103
Author(s):  
Yoshihisa Matsunaga ◽  
Ryoichi Nakamura
Keyword(s):  
Machine Learning ◽  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Real Time ◽  
Invasive Surgery ◽  
Abdominal Cavity ◽  
Training Dataset ◽  
Support Vector ◽  
Processing Cost ◽  
Surgical Field

Background: Abdominal cavity irrigation is a more minimally invasive surgery than that using a gas. Minimally invasive surgery improves the quality of life of patients; however, it demands higher skills from the doctors. Therefore, the study aimed to reduce the burden by assisting and automating the hemostatic procedure a highly frequent procedure by taking advantage of the clearness of the endoscopic images and continuous bleeding point observations in the liquid. We aimed to construct a method for detecting organs, bleeding sites, and hemostasis regions.Methods: We developed a method to perform real-time detection based on machine learning using laparoscopic videos. Our training dataset was prepared from three experiments in pigs. Linear support vector machine was applied using new color feature descriptors. In the verification of the accuracy of the classifier, we performed five-part cross-validation. Classification processing time was measured to verify the real-time property. Furthermore, we visualized the time series class change of the surgical field during the hemostatic procedure.Results: The accuracy of our classifier was 98.3% and the processing cost to perform real-time was enough. Furthermore, it was conceivable to quantitatively indicate the completion of the hemostatic procedure based on the changes in the bleeding region by ablation and the hemostasis regions by tissue coagulation.Conclusions: The organs, bleeding sites, and hemostasis regions classification was useful for assisting and automating the hemostatic procedure in the liquid. Our method can be adapted to more hemostatic procedures. 

Design of a novel robotic system for minimally invasive surgery

2017 ◽  
Vol 44 (3) ◽  
pp. 288-298 ◽  
Author(s):  
Yue Ai ◽  
Bo Pan ◽  
Yili Fu ◽  
Shuguo Wang
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Control Method ◽  
Animal Experiments ◽  
Robotic System ◽  
Robot Assisted ◽  
Content Type ◽  
Hand Eye Coordination ◽  
Control System Architecture

Purpose Robot-assisted system for minimally invasive surgery (MIS) has been attracting more and more attentions. Compared with a traditional MIS, the robot-assisted system for MIS is able to overcome or reduce defects, such as poor hand-eye coordination, heavy labour intensity and limited motion of the instrument. The purpose of this paper is to design a novel robotic system for MIS applications. Design/methodology/approach A robotic system with three separate slave arms for MIS has been designed. In the proposed robot, a new mechanism was designed as the remote centre motion (RCM) mechanism to restrain the movement of instrument or laparoscope around the incision. Moreover, an improved instrument without coupling motion between wrist and grippers was developed to enhance its manipulability. A control system architecture was also developed, and an intuitive control method was applied to realize hand-eye coordination of the operator. Findings For the RCM mechanism, the workspace was analyzed and the positioning accuracy of the remote centre point was tested. The results show that the RCM mechanism can be applied to MIS. Furthermore, the master-slave trajectory tracking experiments reveal that slave robots are able to follow the movement of the master manipulators well. Finally, the feasibility of the robot-assisted system for MIS is proved by performing animal experiments successfully. Originality/value This paper offers a novel robotic system for MIS. It can accomplish the anticipated results.

Real-time instrument detection in minimally invasive surgery using radiofrequency identification technology

2013 ◽  
Vol 185 (2) ◽  
pp. 704-710 ◽  
Author(s):  
Michael Kranzfelder ◽  
Armin Schneider ◽  
Adam Fiolka ◽  
Elena Schwan ◽  
Sonja Gillen ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Real Time ◽  
Invasive Surgery ◽  
Radiofrequency Identification
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