2020 Fourth IEEE International Conference on Robotic Computing (IRC)最新文献_第8页

A New Adaptive Learning algorithm to train Feed-Forward Multi-layer Neural Networks, Applied on Function Approximation Problem 一种新的前馈多层神经网络自适应学习训练算法，应用于函数逼近问题

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00095

Zahra Ghorrati

引用次数: 0

Presenting Botmark: a Computer Benchmark for Service Robotics 介绍Botmark:服务机器人的计算机基准

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00046

Andrew Murtagh, Patrick Lynch, C. McGinn

{"title":"Presenting Botmark: a Computer Benchmark for Service Robotics","authors":"Andrew Murtagh, Patrick Lynch, C. McGinn","doi":"10.1109/IRC.2020.00046","DOIUrl":"https://doi.org/10.1109/IRC.2020.00046","url":null,"abstract":"Central to any robot is a computing system tasked with controlling it; acting as the robot's primary means of computation, its performance significantly impacts the performance of the robot as a whole. Accordingly, developing a rigorous and repeatable methodology to assess the performance of computers in this role is a important step towards improving the performance of robots. For this reason, we present Botmark in the first part of this paper: a benchmark suite designed exclusively for evaluating the performance of computers in the application of mobile service robotics. It comprises seven workloads representing common functionality of mobile service robots including path planning, SLAM, facial recognition, among others. In order to determine the functions to be included, we use the popular RoboCup@Home competition as a proxy for ‘real-world’ robotics applications and derive workloads for the benchmark from the tests in the competition. In the second part of this paper, we demonstrate the potential value of benchmarking tools by conducting an experiment evaluation using Botmark. We firstly make a comparison of various computing platforms representative of those commonly used in robotics and see a wide variability in the performance of each. We then look at the difference in performance between running the benchmark natively, in a virtual machine and in a container. To the extent of the authors' knowledge, this is the first computer benchmarking suite designed to address the area of mobile service robotics extensively. The benchmark is available for free use and we invite the community to use it to evaluate their platforms and submit their results to the authors for dissemination.","PeriodicalId":232817,"journal":{"name":"2020 Fourth IEEE International Conference on Robotic Computing (IRC)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130038943","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: 0

[Copyright notice] (版权)

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/irc.2020.00003

引用次数: 0

Simultaneous shape control and transport with multiple robots 同时形状控制和运输与多个机器人

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00042

G. López-Nicolás, Rafael Herguedas, M. Aranda, Y. Mezouar

引用次数: 6

Hierarchical Planner with Composable Action Models for Asynchronous Parallelization of Tasks and Motions 具有可组合动作模型的任务和动作异步并行化层次规划器

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00029

Bernd Kast, Philipp S. Schmitt, Sebastian Albrecht, W. Feiten, Jianwei Zhang

引用次数: 1

A Quadratic Programming Approach to Modular Robot Control and Motion Planning 模块化机器人控制与运动规划的二次规划方法

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00008

Chao Liu, Mark H. Yim

引用次数: 5

Re-localization for Self-Driving Cars using Semantic Maps 基于语义地图的自动驾驶汽车再定位

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00018

Lhilo Kenye, Rishitha Palugulla, Mehul Arora, Bharath Bhat, R. Kala, Abhijeet Nayak

{"title":"Re-localization for Self-Driving Cars using Semantic Maps","authors":"Lhilo Kenye, Rishitha Palugulla, Mehul Arora, Bharath Bhat, R. Kala, Abhijeet Nayak","doi":"10.1109/IRC.2020.00018","DOIUrl":"https://doi.org/10.1109/IRC.2020.00018","url":null,"abstract":"Localization of vehicle in adverse conditions such as in dense traffic conditions is a challenging problem and state-of-the-art techniques often make the vehicle get lost, requiring a re-localization technique to correctly reset the vehicle pose. The visual place recognition and loop-closure based re-localization techniques need to store a very large map and take a lot of time to re-localize the vehicle. We solve the problem by making a semantic map which is used to re-localize the vehicle, if and once it gets lost by conventional localization techniques. The semantic map is created using a test vehicle with sophisticated sensors, and the map can be used by any vehicle with a stereo camera for re-localization. It is assumed that the test vehicle has a budget stereo camera which produces numerous false positives to be rejected by the re-localizer; while the vehicle also misses many key landmarks during the run due to heavy traffic. These are the challenges which are overcome by the designed re-localization algorithm. The vehicle is tested on a highway scenario in Bengaluru, India for multiple runs in a highway segment. Results confirm accurate re-localization on a semantic map generated from road-signs.","PeriodicalId":232817,"journal":{"name":"2020 Fourth IEEE International Conference on Robotic Computing (IRC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122382515","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

Collaborative Robotics Toolkit (CRTK): Open Software Framework for Surgical Robotics Research 协作机器人工具包(CRTK):外科机器人研究的开放软件框架

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00014

Yun-Hsuan Su, A. Munawar, A. Deguet, Andrew Lewis, Kyle Lindgren, Yangming Li, R. Taylor, G. Fischer, B. Hannaford, P. Kazanzides

{"title":"Collaborative Robotics Toolkit (CRTK): Open Software Framework for Surgical Robotics Research","authors":"Yun-Hsuan Su, A. Munawar, A. Deguet, Andrew Lewis, Kyle Lindgren, Yangming Li, R. Taylor, G. Fischer, B. Hannaford, P. Kazanzides","doi":"10.1109/IRC.2020.00014","DOIUrl":"https://doi.org/10.1109/IRC.2020.00014","url":null,"abstract":"Robot-assisted minimally invasive surgery has made a substantial impact in operating rooms over the past few decades with their high dexterity, small tool size, and impact on adoption of minimally invasive techniques. In recent years, intelligence and different levels of surgical robot autonomy have emerged thanks to the medical robotics endeavors at numerous academic institutions and leading surgical robot companies. To accelerate interaction within the research community and prevent repeated development, we propose the Collaborative Robotics Toolkit (CRTK), a common API for the RAVEN-II and da Vinci Research Kit (dVRK) - two open surgical robot platforms installed at more than 40 institutions worldwide. CRTK has broadened to include other robots and devices, including simulated robotic systems and industrial robots. This common API is a community software infrastructure for research and education in cutting edge human-robot collaborative areas such as semi-autonomous teleoperation and medical robotics. This paper presents the concepts, design details and the integration of CRTK with physical robot systems and simulation platforms.","PeriodicalId":232817,"journal":{"name":"2020 Fourth IEEE International Conference on Robotic Computing (IRC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131635905","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

Stacked BiLSTM - CNN for Multiple label UAV sound classification 基于堆叠BiLSTM - CNN的多标签无人机声音分类

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00089

D. Utebayeva, Manal Alduraibi, L. Ilipbayeva, Yelmurat Temirgaliyev

引用次数: 4

MCC-EKF for Autonomous Car Security 自动驾驶汽车安全MCC-EKF

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00056

Ashutosh Singandhupe, Hung M. La

引用次数: 3