IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation最新文献_第9页

A Fully Actuated Body-Mounted Robotic Assistant for MRI-Guided Low Back Pain Injection. 一种用于MRI引导下腰痛注射的全驱动车载机器人助手。

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-05-01 Epub Date: 2020-09-15 DOI: 10.1109/icra40945.2020.9197534

Gang Li, Niravkumar A Patel, Weiqiang Liu, Di Wu, Karun Sharma, Kevin Cleary, Jan Fritz, Iulian Iordachita

{"title":"A Fully Actuated Body-Mounted Robotic Assistant for MRI-Guided Low Back Pain Injection.","authors":"Gang Li, Niravkumar A Patel, Weiqiang Liu, Di Wu, Karun Sharma, Kevin Cleary, Jan Fritz, Iulian Iordachita","doi":"10.1109/icra40945.2020.9197534","DOIUrl":"10.1109/icra40945.2020.9197534","url":null,"abstract":"This paper reports the development of a fully actuated body-mounted robotic assistant for MRI-guided low back pain injection. The robot is designed with a 4-DOF needle alignment module and a 2-DOF remotely actuated needle driver module. The 6-DOF fully actuated robot can operate inside the scanner bore during imaging; hence, minimizing the need of moving the patient in or out of the scanner during the procedure, and thus potentially reducing the procedure time and streamlining the workflow. The robot is built with a lightweight and compact structure that can be attached directly to the patient's lower back using straps; therefore, attenuating the effect of patient motion by moving with the patient. The novel remote actuation design of the needle driver module with beaded chain transmission can reduce the weight and profile on the patient, as well as minimize the imaging degradation caused by the actuation electronics. The free space positioning accuracy of the system was evaluated with an optical tracking system, demonstrating the mean absolute errors (MAE) of the tip position to be 0.99±0.46 mm and orientation to be 0.99±0.65°. Qualitative imaging quality evaluation was performed on a human volunteer, revealing minimal visible image degradation that should not affect the procedure. The mounting stability of the system was assessed on a human volunteer, indicating the 3D position variation of target movement with respect to the robot frame to be less than 0.7 mm.","PeriodicalId":73286,"journal":{"name":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","volume":"2020 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/icra40945.2020.9197534","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39348468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Large-Scale Volumetric Scene Reconstruction using LiDAR 基于激光雷达的大规模体景重建

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9197388

Tilman Kuhner, Julius Kummerle

{"title":"Large-Scale Volumetric Scene Reconstruction using LiDAR","authors":"Tilman Kuhner, Julius Kummerle","doi":"10.1109/ICRA40945.2020.9197388","DOIUrl":"https://doi.org/10.1109/ICRA40945.2020.9197388","url":null,"abstract":"Large-scale 3D scene reconstruction is an important task in autonomous driving and other robotics applications as having an accurate representation of the environment is necessary to safely interact with it. Reconstructions are used for numerous tasks ranging from localization and mapping to planning. In robotics, volumetric depth fusion is the method of choice for indoor applications since the emergence of commodity RGB-D cameras due to its robustness and high reconstruction quality. In this work we present an approach for volumetric depth fusion using LiDAR sensors as they are common on most autonomous cars. We present a framework for large-scale mapping of urban areas considering loop closures. Our method creates a meshed representation of an urban area from recordings over a distance of 3.7km with a high level of detail on consumer graphics hardware in several minutes. The whole process is fully automated and does not need any user interference. We quantitatively evaluate our results from a real world application. Also, we investigate the effects of the sensor model that we assume on reconstruction quality by using synthetic data.","PeriodicalId":73286,"journal":{"name":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","volume":"39 1","pages":"6261-6267"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82884048","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: 1

Mechanism and Model of a Soft Robot for Head Stabilization in Cancer Radiation Therapy. 肿瘤放射治疗中头部稳定软机器人的机理与模型。

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-05-01 Epub Date: 2020-09-15 DOI: 10.1109/icra40945.2020.9197007

Olalekan Ogunmolu, Xinmin Liu, Nicholas Gans, Rodney D Wiersma

引用次数: 1

Unified Intrinsic and Extrinsic Camera and LiDAR Calibration under Uncertainties 不确定条件下相机和激光雷达内、外统一标定

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9197496

Julius Kummerle, Tilman Kuhner

引用次数: 22

Contact Stability Analysis of Magnetically-Actuated Robotic Catheter Under Surface Motion. 磁动机器人导管在表面运动下的接触稳定性分析

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-05-01 Epub Date: 2020-09-15 DOI: 10.1109/icra40945.2020.9196951

Ran Hao, Tipakorn Greigarn, M Cenk Çavuşoğlu

引用次数: 0

Design and Analysis of a Synergy-Inspired Three-Fingered Hand 协同启发的三指手的设计与分析

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-05-01 DOI: 10.1109/ICRA40945.2020.9196901

Chen Wenrui, Xia Zhilan, Lu Jingwen, Zhao Zilong, W. Yao-nan

引用次数: 4

High-Resolution Optical Fiber Shape Sensing of Continuum Robots: A Comparative Study. 连续体机器人高分辨率光纤形状传感的比较研究。

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-05-01 Epub Date: 2020-09-15 DOI: 10.1109/icra40945.2020.9197454

Frederic Monet, Shahriar Sefati, Pierre Lorre, Arthur Poiffaut, Samuel Kadoury, Mehran Armand, Iulian Iordachita, Raman Kashyap

{"title":"High-Resolution Optical Fiber Shape Sensing of Continuum Robots: A Comparative Study.","authors":"Frederic Monet, Shahriar Sefati, Pierre Lorre, Arthur Poiffaut, Samuel Kadoury, Mehran Armand, Iulian Iordachita, Raman Kashyap","doi":"10.1109/icra40945.2020.9197454","DOIUrl":"https://doi.org/10.1109/icra40945.2020.9197454","url":null,"abstract":"Flexible medical instruments, such as Continuum Dexterous Manipulators (CDM), constitute an important class of tools for minimally invasive surgery. Accurate CDM shape reconstruction during surgery is of great importance, yet a challenging task. Fiber Bragg grating (FBG) sensors have demonstrated great potential in shape sensing and consequently tip position estimation of CDMs. However, due to the limited number of sensing locations, these sensors can only accurately recover basic shapes, and become unreliable in the presence of obstacles or many inflection points such as s-bends. Optical Frequency Domain Reflectometry (OFDR), on the other hand, can achieve much higher spatial resolution, and can therefore accurately reconstruct more complex shapes. Additionally, Random Optical Gratings by Ultraviolet laser Exposure (ROGUEs) can be written in the fibers to increase signal to noise ratio of the sensors. In this comparison study, the tip position error is used as a metric to compare both FBG and OFDR shape reconstructions for a 35 mm long CDM developed for orthopedic surgeries, using a pair of stereo cameras as ground truth. Three sets of experiments were conducted to measure the accuracy of each technique in various surgical scenarios. The tip position error for the OFDR (and FBG) technique was found to be 0.32 (0.83) mm in free-bending environment, 0.41 (0.80) mm when interacting with obstacles, and 0.45 (2.27) mm in s-bending. Moreover, the maximum tip position error remains sub-millimeter for the OFDR reconstruction, while it reaches 3.40 mm for FBG reconstruction. These results propose a cost-effective, robust and more accurate alternative to FBG sensors for reconstructing complex CDM shapes.","PeriodicalId":73286,"journal":{"name":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","volume":"2020 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/icra40945.2020.9197454","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39335086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Autonomously Navigating a Surgical Tool Inside the Eye by Learning from Demonstration. 通过示范学习在眼内自主导航手术工具。

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-05-01 Epub Date: 2020-09-15 DOI: 10.1109/icra40945.2020.9196537

Ji Woong Kim, Changyan He, Muller Urias, Peter Gehlbach, Gregory D Hager, Iulian Iordachita, Marin Kobilarov

{"title":"Autonomously Navigating a Surgical Tool Inside the Eye by Learning from Demonstration.","authors":"Ji Woong Kim, Changyan He, Muller Urias, Peter Gehlbach, Gregory D Hager, Iulian Iordachita, Marin Kobilarov","doi":"10.1109/icra40945.2020.9196537","DOIUrl":"https://doi.org/10.1109/icra40945.2020.9196537","url":null,"abstract":"A fundamental challenge in retinal surgery is safely navigating a surgical tool to a desired goal position on the retinal surface while avoiding damage to surrounding tissues, a procedure that typically requires tens-of-microns accuracy. In practice, the surgeon relies on depth-estimation skills to localize the tool-tip with respect to the retina in order to perform the tool-navigation task, which can be prone to human error. To alleviate such uncertainty, prior work has introduced ways to assist the surgeon by estimating the tool-tip distance to the retina and providing haptic or auditory feedback. However, automating the tool-navigation task itself remains unsolved and largely unexplored. Such a capability, if reliably automated, could serve as a building block to streamline complex procedures and reduce the chance for tissue damage. Towards this end, we propose to automate the tool-navigation task by learning to mimic expert demonstrations of the task. Specifically, a deep network is trained to imitate expert trajectories toward various locations on the retina based on recorded visual servoing to a given goal specified by the user. The proposed autonomous navigation system is evaluated in simulation and in physical experiments using a silicone eye phantom. We show that the network can reliably navigate a needle surgical tool to various desired locations within 137 μm accuracy in physical experiments and 94 μm in simulation on average, and generalizes well to unseen situations such as in the presence of auxiliary surgical tools, variable eye backgrounds, and brightness conditions.","PeriodicalId":73286,"journal":{"name":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","volume":"2020 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/icra40945.2020.9196537","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39520516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20

Enhancing Imbalanced Dataset by Utilizing (K-NN Based SMOTE_3D Algorithm) 利用（基于K-NN的SMOTE_3D算法）增强不平衡数据集

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-04-25 DOI: 10.17352/ARA.000002

Khaldoon Alshouiliy, Sujan Ray, A. Al-Ghamdi, D. Agrawal

{"title":"Enhancing Imbalanced Dataset by Utilizing (K-NN Based SMOTE_3D Algorithm)","authors":"Khaldoon Alshouiliy, Sujan Ray, A. Al-Ghamdi, D. Agrawal","doi":"10.17352/ARA.000002","DOIUrl":"https://doi.org/10.17352/ARA.000002","url":null,"abstract":"Big data is currently a huge industry that has grown significantly every year. Big data is being used by machine learning and deep learning algorithm to study, analyze and parse big data and then drive useful and beneficial results. However, most of the real datasets are collected through different organizations and social media and mainly fall under the category of Big Data applications. One of the biggest and most drawbacks of such datasets is an imbalance representation of samples from different categories. In such case, the classifiers and deep learning techniques are not capable of handling issues like these. A majority of existing works tend to overlook these issues. Typical data balancing methods in the literature resort to data resampling whether it is under sampling a majority class samples or oversampling the minority class of samples. In this work, we focus on the minority sample and ignore the majority ones. Many researchers have done many works as most of the work suffers from over sampling or form the generated noise in the dataset. Additionally, works are either suitable for either big data or small data. Moreover, some other work suffers from a long processing time as complicated algorithms are used with many steps to fix the imbalance problem. Therefore, we introduce a new algorithm that deals with all these issues. We have created a short example to explain briefly how the SMOTE works and why we need to enhance the SMOTE and we have done this by using a very well-known imbalance dataset that we downloaded from the Kaggle website. We collect the results by using Azure machine learning platform. Then, we compare the results to see that the model is functional just good with SMOTE and way better than without it.","PeriodicalId":73286,"journal":{"name":"IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation","volume":"4 1","pages":"001-006"},"PeriodicalIF":0.0,"publicationDate":"2020-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42631685","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: 1

Estimation of nonlinear systems parameters 非线性系统参数的估计

IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation Pub Date : 2020-03-01 DOI: 10.11591/ijra.v9i1.pp26-33

Mohamed Benyassi, A. Brouri

引用次数: 0