Autonomous Flexible Endoscope for Minimally Invasive Surgery With Enhanced Safety

Ma, Xiaoyi; Song, Chengqun; Chiu, Philip Wai‐Yan; Li, Zheng

doi:10.1109/lra.2019.2895273

Cited by 67 publications

(36 citation statements)

References 22 publications

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“…Some of them also include haptic feedback, which intensifies enormously the immersive experience of the surgeon in the actual intervention. In addition, important ergonomic improvements from the surgeons point of view are achieved with robotic surgery systems when compared with traditional procedures [11], [12], [26], [27]. The feasibility of robotic-assisted minimally invasive procedures has been demonstrated in different types of interventions [28]- [30].…”

Section: State Of the Art A Surgical Robotsmentioning

confidence: 99%

Position Based Model of a Flexible Ureterorenoscope in a Virtual Reality Training Platform for a Minimally Invasive Surgical Robot

et al. 2019

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Although the total number of ureteroscopy interventions during the past years has significantly increased, current flexible ureteroscopy procedures still present some limitations to urologic surgeons. However, nowadays different robotic systems have been developed in order to reduce those limitations. Flexible ureteroscopy robots provide a technological alternative which combines the benefits that this type of procedures offers to the patients, and solutions to the problems encountered from the surgeons perspective. In this paper, a virtual reality training platform for robot-assisted flexible ureterorenoscopy interventions is presented. A position based model for the virtual flexible endoscope is detailed and a standard user interface for the training platform is designed. Moreover, a comparative analysis of the performance of the training platform in different scenarios, including the navigation through a three-dimensional ureterorenal model, is presented. The obtained results determine that the training platform presents different computational rates depending on the complexity of the implemented environment and on the number of collisions and constraints that have to be handled. Nevertheless, the virtual model is visually plausible, effective for real-time user interaction and suitable for training.

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Section: State Of the Art A Surgical Robotsmentioning

confidence: 99%

Position Based Model of a Flexible Ureterorenoscope in a Virtual Reality Training Platform for a Minimally Invasive Surgical Robot

et al. 2019

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“…The surgeon's RoA at the current moment is calculated by analyzing the current segmented instrument locations and the estimated surgeon's attention focus from the headset's gyroscope. The awareness of the surgeon's attention focus makes the proposed method favorable compared to available solutions, such as marker tracking [27], desired camera position tagging using surgical tool's tip [28] or keeping tools within the desired image frame [29].…”

Section: Introductionmentioning

confidence: 99%

Autonomous Endoscope Robot Positioning Using Instrument Segmentation With Virtual Reality Visualization

Zinchenko

Song

2021

IEEE Access

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This paper presents a method for endoscope's autonomous positioning by a robotic endoscope holder for minimally invasive surgery. The method improves human-robot cooperation in robot-assisted surgery by allowing the endoscope holder to acknowledge the surgeon's view projection and navigate the camera without manual control. The real-time prediction of next desired camera location is estimated using segmented instrument's tip locations from endoscope video and surgeon's attention focus given by tracked virtual reality headset. To tackle the issue of real-time surgical instrument segmentation for more precise instrument tip localization, we propose the YOLOv3 and ResNet Combined Neural Network. The method showed an 86.6% IoU across MICCAI'17 Endovis datasets with 30 frames per second processing speed. The proposed pipeline was implemented in ROS on Ubuntu with visualization running under Windows operating system in Unity3D. The simulation demonstrates the robotic arm, endoscope, and surgical environment visualized in 3D in the virtual reality headset to provide a stable view of the endoscope and improve the surgeon's perception of the operating environment.INDEX TERMS autonomous robot control, artificial neural network, minimally invasive surgery, object segmentation, human-robot cooperation.

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“…Hwang and Kwon proposed a novel constrained strong continuum manipulator by using auxiliary links attached to the main continuum links [13]. Li et al developed a flexible endoscope based on the tendon-driven continuum mechanism [14]. The wrist joints of an end-effector are usually actuated by several long-distance cables with a small diameter.…”

Section: Introductionmentioning

confidence: 99%

A Clamping Force Estimation Method Based on a Joint Torque Disturbance Observer Using PSO-BPNN for Cable-Driven Surgical Robot End-Effectors

Wang

Chen

et al. 2019

Sensors

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The ability to sense external force is an important technique for force feedback, haptics and safe interaction control in minimally-invasive surgical robots (MISRs). Moreover, this ability plays a significant role in the restricting refined surgical operations. The wrist joints of surgical robot end-effectors are usually actuated by several long-distance wire cables. Its two forceps are each actuated by two cables. The scope of force sensing includes multidimensional external force and one-dimensional clamping force. This paper focuses on one-dimensional clamping force sensing method that do not require any internal force sensor integrated in the end-effector’s forceps. A new clamping force estimation method is proposed based on a joint torque disturbance observer (JTDO) for a cable-driven surgical robot end-effector. The JTDO essentially considers the variations in cable tension between the actual cable tension and the estimated cable tension using a Particle Swarm Optimization Back Propagation Neural Network (PSO-BPNN) under free motion. Furthermore, a clamping force estimator is proposed based on the forceps’ JTDO and their mechanical relations. According to comparative analyses in experimental studies, the detection resolutions of collision force and clamping force were 0.11 N. The experimental results verify the feasibility and effectiveness of the proposed clamping force sensing method.

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Autonomous Flexible Endoscope for Minimally Invasive Surgery With Enhanced Safety

Cited by 67 publications

References 22 publications

Position Based Model of a Flexible Ureterorenoscope in a Virtual Reality Training Platform for a Minimally Invasive Surgical Robot

Position Based Model of a Flexible Ureterorenoscope in a Virtual Reality Training Platform for a Minimally Invasive Surgical Robot

Autonomous Endoscope Robot Positioning Using Instrument Segmentation With Virtual Reality Visualization

A Clamping Force Estimation Method Based on a Joint Torque Disturbance Observer Using PSO-BPNN for Cable-Driven Surgical Robot End-Effectors

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