2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)最新文献

A proposed mapping method for aligning machine execution data to numerical control code 提出了一种将机床执行数据与数控代码对齐的映射方法

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-09-23 DOI: 10.1109/COASE.2019.8842832

Laetitia V. Monnier, William Z. Bemstein, S. Foufou

引用次数: 3

optimizing outpatient Department Staffing Level using Multi-Fidelity Models 利用多保真度模型优化门诊人员配置水平

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-09-19 DOI: 10.1109/COASE.2019.8842984

Bowen Pang, Xiaolei Xie, B. Heidergott, Yijie Peng

{"title":"optimizing outpatient Department Staffing Level using Multi-Fidelity Models","authors":"Bowen Pang, Xiaolei Xie, B. Heidergott, Yijie Peng","doi":"10.1109/COASE.2019.8842984","DOIUrl":"https://doi.org/10.1109/COASE.2019.8842984","url":null,"abstract":"The workload of the outpatient departments in Chinese large hospitals is extremely high. Patients often have to wait for a long time before getting their treatments. It is economically expensive to increase medical staffs including nurses and doctors. Therefore, it is critical to optimize staff planning in the outpatient departments to reduce excessive patient waiting time. A high-fidelity simulation model can accurately capture the features of the outpatient service system. But it is very time-consuming to obtain the optimal staff planning decision only based on the simulation model. A simplified queueing model might lead to an analytical solution for the optimal staff planning problem, but it can not fully capture the feature of the real outpatient service system. We propose to use the outputs of the high-fidelity simulation model to drive the output of the low-fidelity queueing model closer to that of the outpatient service system, and then use the data-driven queueing model to make the staff planning decision. Empirical studies on a major hospital are carried out, which demonstrate the effectiveness and efficiency of our method.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"31 1","pages":"715-720"},"PeriodicalIF":0.0,"publicationDate":"2019-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72850412","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

Advanced Sensor and Target Development to Support Robot Accuracy Degradation Assessment 支持机器人精度退化评估的先进传感器和目标开发

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-26 DOI: 10.1109/COASE.2019.8843200

Guixiu Qiao

{"title":"Advanced Sensor and Target Development to Support Robot Accuracy Degradation Assessment","authors":"Guixiu Qiao","doi":"10.1109/COASE.2019.8843200","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843200","url":null,"abstract":"This paper presents a vision-based, 6 degree of freedom (DOF) measurement system that can measure robot dynamic motions in real-time. A motorized target is designed as a part of the system to work with a vision-based measurement instrument, providing unique features to stand out from the background and enable the achievement of high accuracy monitored, assessed, and predicted to avoid a costly, unexpected shutdown, or decrease in manufacturing quality and production efficiency. The National Institute of Standards and Technology (NIST) is developing the necessary measurement science to support the monitoring, diagnostics, and prognostics of robot systems by providing intelligence to enhance maintenance and control strategies. The robot accuracy degradation research includes the development of modeling and algorithm for the test method, advanced sensor and target development to accurately measure robot 6 DOF information, and algorithms to analyze the data. This paper focuses on the development of the advanced sensor and target. A use case shows the use of the measurement system on a Universal Robot to support the robot accuracy degradation assessment.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"39 1","pages":"54-59"},"PeriodicalIF":0.0,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80941169","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: 7

Multi-Task Hierarchical Imitation Learning for Home Automation 面向家庭自动化的多任务分层模仿学习

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-25 DOI: 10.1109/COASE.2019.8843293

Roy Fox, R. Berenstein, I. Stoica, Ken Goldberg

{"title":"Multi-Task Hierarchical Imitation Learning for Home Automation","authors":"Roy Fox, R. Berenstein, I. Stoica, Ken Goldberg","doi":"10.1109/COASE.2019.8843293","DOIUrl":"https://doi.org/10.1109/COASE.2019.8843293","url":null,"abstract":"Control policies for home automation robots can be learned from human demonstrations, and hierarchical control has the potential to reduce the required number of demonstrations. When learning multiple policies for related tasks, demonstrations can be reused between the tasks to further reduce the number of demonstrations needed to learn each new policy. We present HIL-MT, a framework for Multi-Task Hierarchical Imitation Learning, involving a human teacher, a networked Toyota HSR robot, and a cloud-based server that stores demonstrations and trains models. In our experiments, HIL-MT learns a policy for clearing a table of dishes from 11.2 demonstrations on average. Learning to set the table requires 19 new demonstrations when training separately, but only 11.6 new demonstrations when also reusing demonstrations of clearing the table. HIL-MT learns policies for building 3- and 4-level pyramids of glass cups from 8.2 and 5 demonstrations, respectively, but reusing the 3-level demonstrations for learning a 4-level policy only requires 2.7 new demonstrations. These results suggest that learning hierarchical policies for structured domestic tasks can reuse existing demonstrations of related tasks to reduce the need for new demonstrations.","PeriodicalId":6695,"journal":{"name":"2019 IEEE 15th International Conference on Automation Science and Engineering (CASE)","volume":"39 2 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2019-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87674519","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: 23

Deep Reinforcement Learning of Robotic Precision Insertion Skill Accelerated by Demonstrations 机器人精密插入技能的深度强化学习

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-21 DOI: 10.1109/COASE.2019.8842940

Xiapeng Wu, Dapeng Zhang, Fangbo Qin, De Xu

引用次数: 14

Automatic Fingertip Exchange System for Robotic Grasping in Flexible Production Processes 柔性生产过程中机器人抓取的自动指尖交换系统

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-19 DOI: 10.1109/COASE.2019.8842911

Aljaz Kramberger, A. Wolniakowski, Mads Høj Rasmussen, M. Munih, A. Ude, Christian Schlette

引用次数: 10

What are the Most Informative Data for Virtual Metrology? A use case on Multi-Stage Processes Fault Prediction 虚拟计量最有用的数据是什么?多阶段流程故障预测用例

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8842942

Marco Maggipinto, Gian Antonio Susto, Federico Zocco, S. McLoone

引用次数: 1

CASE 2019 Welcome Message from Program Chair 项目主席欢迎辞

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/coase.2019.8843067

引用次数: 0

Optical In-Situ Verification of 3D-Printed Electronic Circuits 3d打印电子电路的光学原位验证

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8842835

Florens Wasserfall, Daniel Ahlers, N. Hendrich

引用次数: 8

A Distributed Control Approach Based on Game Theory for the Optimal Energy Scheduling of a Residential Microgrid with Shared Generation and Storage 基于博弈论的住宅微电网共享发电和共享储能最优能量调度分布式控制方法

2019 IEEE 15th International Conference on Automation Science and Engineering (CASE) Pub Date : 2019-08-01 DOI: 10.1109/COASE.2019.8843141

Raffaele Carli, M. Dotoli, Vittorio Palmisano

引用次数: 6