2021 International Symposium on Medical Robotics (ISMR)最新文献_第4页

A Pneumatic Optical Soft Sensor for Fingertip Force Sensing 一种用于指尖力传感的气动光学软传感器

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-11-17 DOI: 10.1109/ismr48346.2021.9661559

Le Chen, Boshen Qi, Jun Sheng

引用次数: 0

Prototyping a sensorized tool wristband for objective skill assessment and feedback during training in minimally invasive surgery 一种用于微创手术训练中客观技能评估和反馈的传感工具腕带原型

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-11-17 DOI: 10.1109/ismr48346.2021.9661567

A. Mariani, Matteo Conti, S. Gandah, C. G. D. Paratesi, A. Menciassi

引用次数: 0

Robot Force Estimation with Learned Intraoperative Correction 机器人力估计与习得术中校正

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-11-17 DOI: 10.1109/ismr48346.2021.9661568

J. Wu, Nural Yilmaz, U. Tumerdem, P. Kazanzides

{"title":"Robot Force Estimation with Learned Intraoperative Correction","authors":"J. Wu, Nural Yilmaz, U. Tumerdem, P. Kazanzides","doi":"10.1109/ismr48346.2021.9661568","DOIUrl":"https://doi.org/10.1109/ismr48346.2021.9661568","url":null,"abstract":"Measurement of environment interaction forces during robotic minimally-invasive surgery would enable haptic feedback to the surgeon, thereby solving one long-standing limitation. Estimating this force from existing sensor data avoids the challenge of retrofitting systems with force sensors, but is difficult due to mechanical effects such as friction and compliance in the robot mechanism. We have previously shown that neural networks can be trained to estimate the internal robot joint torques, thereby enabling estimation of external forces on the da Vinci Research Kit (dVRK). In this work, we extend the method to estimate external Cartesian forces and torques, and also present a two-step approach to adapt to the specific surgical setup by compensating for forces due to the interactions between the instrument shaft and cannula seal and between the trocar and patient body. Experiments show that this approach provides estimates of external forces and torques within a mean root-mean-square error (RMSE) of 1.8N and 0.1Nm, respectively. Furthermore, the two-step approach can add as little as 5 minutes to the surgery setup time, with about 4 minutes to collect intraoperative training data and 1 minute to train the second-step network.","PeriodicalId":405817,"journal":{"name":"2021 International Symposium on Medical Robotics (ISMR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122944924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Homography-based Visual Servoing with Remote Center of Motion for Semi-autonomous Robotic Endoscope Manipulation 半自主机器人内窥镜操作的远程运动中心视觉伺服

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-10-25 DOI: 10.1109/ISMR48346.2021.9661563

M. Huber, John Bason Mitchell, Ross Henry, S. Ourselin, Tom Kamiel Magda Vercauteren, C. Bergeles

{"title":"Homography-based Visual Servoing with Remote Center of Motion for Semi-autonomous Robotic Endoscope Manipulation","authors":"M. Huber, John Bason Mitchell, Ross Henry, S. Ourselin, Tom Kamiel Magda Vercauteren, C. Bergeles","doi":"10.1109/ISMR48346.2021.9661563","DOIUrl":"https://doi.org/10.1109/ISMR48346.2021.9661563","url":null,"abstract":"The dominant visual servoing approaches in Minimally Invasive Surgery (MIS) follow single points or adapt the endoscope’s field of view based on the surgical tools’ distance. These methods rely on point positions with respect to the camera frame to infer a control policy. Deviating from the dominant methods, we formulate a robotic controller that allows for image-based visual servoing that requires neither explicit tool and camera positions nor any explicit image depth information. The proposed method relies on homography-based image registration, which changes the automation paradigm from point-centric towards surgical-scene-centric approach. It simultaneously respects a programmable Remote Center of Motion (RCM). Our approach allows a surgeon to build a graph of desired views, from which, once built, views can be manually selected and automatically servoed to irrespective of robot-patient frame transformation changes. We evaluate our method on an abdominal phantom and provide an open source ROS Moveit integration for use with any serial manipulator 3. A video is provided 4.","PeriodicalId":405817,"journal":{"name":"2021 International Symposium on Medical Robotics (ISMR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114545883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Toward Learning Context-Dependent Tasks from Demonstration for Tendon-Driven Surgical Robots 从肌腱驱动手术机器人的演示中学习上下文相关任务

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-10-15 DOI: 10.1109/ismr48346.2021.9661534

Yixuan Huang, Michael Bentley, Tucker Hermans, A. Kuntz

引用次数: 2

Planning Sensing Sequences for Subsurface 3D Tumor Mapping 面向地下三维肿瘤映射的传感序列规划

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-10-12 DOI: 10.1109/ismr48346.2021.9661488

Brian Y. Cho, Tucker Hermans, A. Kuntz

引用次数: 1

Learning from Demonstrations for Autonomous Soft-tissue Retraction * 从自主软组织牵入演示中学习*

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-10-01 DOI: 10.1109/ismr48346.2021.9661514

Ameya Pore, E. Tagliabue, M. Piccinelli, D. Dall’Alba, A. Casals, P. Fiorini

{"title":"Learning from Demonstrations for Autonomous Soft-tissue Retraction *","authors":"Ameya Pore, E. Tagliabue, M. Piccinelli, D. Dall’Alba, A. Casals, P. Fiorini","doi":"10.1109/ismr48346.2021.9661514","DOIUrl":"https://doi.org/10.1109/ismr48346.2021.9661514","url":null,"abstract":"The current research focus in Robot-Assisted Minimally Invasive Surgery (RAMIS) is directed towards increasing the level of robot autonomy, to place surgeons in a supervisory position. Although Learning from Demonstrations (LfD) approaches are among the preferred ways for an autonomous surgical system to learn expert gestures, they require a high number of demonstrations and show poor generalization to the variable conditions of the surgical environment. In this work, we propose an LfD methodology based on Generative Adversarial Imitation Learning (GAIL) that is built on a Deep Reinforcement Learning (DRL) setting. GAIL combines generative adversarial networks to learn the distribution of expert trajectories with a DRL setting to ensure generalisation of trajectories providing human-like behaviour. We consider automation of tissue retraction, a common RAMIS task that involves soft tissues manipulation to expose a region of interest. In our proposed methodology, a small set of expert trajectories can be acquired through the da Vinci Research Kit (dVRK) and used to train the proposed LfD method inside a simulated environment. Results indicate that our methodology can accomplish the tissue retraction task with human-like behaviour while being more sample-efficient than the baseline DRL method. Towards the end, we show that the learnt policies can be successfully transferred to the real robotic platform and deployed for soft tissue retraction on a synthetic phantom.","PeriodicalId":405817,"journal":{"name":"2021 International Symposium on Medical Robotics (ISMR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124776690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 17

From Bench to Bedside: The First Live Robotic Surgery on the dVRK to Enable Remote Telesurgery with Motion Scaling 从工作台到床边:dVRK上的第一个实时机器人手术，使远程手术与运动缩放成为可能

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-09-24 DOI: 10.1109/ismr48346.2021.9661536

Florian Richter, E. Funk, Won Seo Park, R. Orosco, Michael C. Yip

{"title":"From Bench to Bedside: The First Live Robotic Surgery on the dVRK to Enable Remote Telesurgery with Motion Scaling","authors":"Florian Richter, E. Funk, Won Seo Park, R. Orosco, Michael C. Yip","doi":"10.1109/ismr48346.2021.9661536","DOIUrl":"https://doi.org/10.1109/ismr48346.2021.9661536","url":null,"abstract":"Innovations from surgical robotic research rarely translates to live surgery due to the significant difference between the lab and a live environment. Live environments require considerations that are often overlooked during early stages of research such as surgical staff, surgical procedure, and the challenges of working with live tissue. One such example is the da Vinci Research Kit (dVRK) which is used by over 40 robotics research groups and represents an open-sourced version of the da Vinci ® Surgical System. Despite dVRK being available for nearly a decade and the ideal candidate for translating research to practice on over 5,000 da Vinci ® Systems used in hospitals around the world, not one live surgery has been conducted with it. In this paper, we address the challenges, considerations, and solutions for translating surgical robotic research from bench-to-bedside. This is explained from the perspective of a remote telesurgery scenario where motion scaling solutions previously experimented in a lab setting are translated to a live pig surgery. This study presents results from the first ever use of a dVRK in a live animal and discusses how the surgical robotics community can approach translating their research to practice.","PeriodicalId":405817,"journal":{"name":"2021 International Symposium on Medical Robotics (ISMR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124382778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Autonomous tissue retraction with a biomechanically informed logic based framework 自主组织收缩与生物力学知情逻辑为基础的框架

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-09-06 DOI: 10.1109/ismr48346.2021.9661573

D. Meli, E. Tagliabue, D. Dall’Alba, P. Fiorini

{"title":"Autonomous tissue retraction with a biomechanically informed logic based framework","authors":"D. Meli, E. Tagliabue, D. Dall’Alba, P. Fiorini","doi":"10.1109/ismr48346.2021.9661573","DOIUrl":"https://doi.org/10.1109/ismr48346.2021.9661573","url":null,"abstract":"Autonomy in robot-assisted surgery is essential to reduce surgeons’ cognitive load and eventually improve the overall surgical outcome. A key requirement for autonomy in a safety-critical scenario as surgery lies in the generation of interpretable plans that rely on expert knowledge. Moreover, the Autonomous Robotic Surgical System (ARSS) must be able to reason on the dynamic and unpredictable anatomical environment, and quickly adapt the surgical plan in case of unexpected situations. In this paper, we present a modular Framework for Robot-Assisted Surgery (FRAS) in deformable anatomical environments. Our framework integrates a logic module for task-level interpretable reasoning, a biomechanical simulation that complements data from real sensors, and a situation awareness module for context interpretation. The framework performance is evaluated on simulated soft tissue retraction, a common surgical task to remove the tissue hiding a region of interest. Results show that the framework has the adaptability required to successfully accomplish the task, handling dynamic environmental conditions and possible failures, while guaranteeing the computational efficiency required in a real surgical scenario. The framework is made publicly available.","PeriodicalId":405817,"journal":{"name":"2021 International Symposium on Medical Robotics (ISMR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125201845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Toward Robotically Automated Femoral Vascular Access 迈向机器人自动化股骨血管通路

2021 International Symposium on Medical Robotics (ISMR) Pub Date : 2021-07-06 DOI: 10.1109/ismr48346.2021.9661560

N. Zevallos, Evan Harber, Abhimanyu, K. Patel, Yizhu Gu, Kenny Sladick, F. Guyette, L. Weiss, M. Pinsky, H. Gómez, J. Galeotti, H. Choset

引用次数: 7