2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)最新文献_第3页

The Ecological Model and Global optimization Algorithm for Service Internet 服务型互联网生态模型及全局优化算法

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216876

Zhixuan Jia, Shuangxi Huang, Yushun Fan

{"title":"The Ecological Model and Global optimization Algorithm for Service Internet","authors":"Zhixuan Jia, Shuangxi Huang, Yushun Fan","doi":"10.1109/CASE48305.2020.9216876","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9216876","url":null,"abstract":"With the further development of service Internet, how to effectively manage, control and optimize the entire service Internet system has become a research hotspot. However, the current research on service Internet optimization mostly focuses on service selection and service composition. And few studies have provided the global optimization strategy for service Internet. So, in this paper, first of all, we propose an ecological model of service Internet by using ecological theory and business process characteristics. Then, based on this model, considering the time-varying uncertainty of service demands, a global service Internet optimization policy learning algorithm called GSIOA is proposed, which uses deep reinforcement learning to automatically formulate global management, control, and optimization strategies of service Internet. Finally, through the comparison of simulation results, it can be concluded that the performance of GSIOA is better than other baseline methods. Our algorithm based on deep reinforcement learning can well solve the global optimization problem of service Internet.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132718924","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

Review of Classification for Wall Climbing Robots for Industrial Inspection Applications 工业检测爬壁机器人分类综述

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216878

Ahmad Hajeer, Lei Chen, E. Hu

{"title":"Review of Classification for Wall Climbing Robots for Industrial Inspection Applications","authors":"Ahmad Hajeer, Lei Chen, E. Hu","doi":"10.1109/CASE48305.2020.9216878","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9216878","url":null,"abstract":"A new methodology that mixes the already well-established classifications of Wall Climbing Robots (WCR) based on locomotion and attachment is proposed. The need for industrial inspections of processing assets, with vertical flat surfaces, like tanks and pressure vessels that are continuously exposed to fatigue, corrosion and erosion are identified. The types of industrial inspections tasks vary in a wide range from, Visual Inspections (VI) and Non-Destructive Testing (NDT) to cleaning and repair. Mobile robots are used to perform inspection tasks. There are few commercial WCR that are available for industrial applications. The classification method is based on locomotion mechanisms, and attachment techniques rather than classical classification assumed in all previous reviews of WCR. A general design framework is suggested to derive the custom-building design of the inspection WCR. The performance of the WCR is compared against the main features of maximum speed and payload capacity. The main locomotion types are wheeled (W), tracked (T), walking (L) and hybrid (H). The primary attachment methods are magnetic (G), pneumatic (P), mechanical (M), electrostatic (E), chemical (C) and hybrid (H). As another application, the classification is used to identify and differentiate WCR from other types of Climbing Robots (CR) to cover almost all kinds of WCR. In addition, the classification can be employed in the customisation of WCR that are built to perform specialised inspection tasks. The customisation of WCR results from the need for simplicity in their structure, adapting testing equipment and improving operations.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133191522","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

Industrial Blockchain of Things: A Solution for Trustless Industrial Data Sharing and Beyond 工业物链:无信任工业数据共享及其他解决方案

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216817

Zheng Zhang, Liang Huang, Renzhong Tang, T. Peng, Lihang Guo, Xingwei Xiang

{"title":"Industrial Blockchain of Things: A Solution for Trustless Industrial Data Sharing and Beyond","authors":"Zheng Zhang, Liang Huang, Renzhong Tang, T. Peng, Lihang Guo, Xingwei Xiang","doi":"10.1109/CASE48305.2020.9216817","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9216817","url":null,"abstract":"Industrial Internet of Things (IIoT) is regarded as a promising transformation technology for manufacturing industry. We expect the information flow through along the process of material flow, gauging and collective devices feed IIoT platform with essential data. AI and big data analytical techniques can then be used to process the data to support a series of decision-making. Users at both managerial and operational levels can take actions accordingly, which significantly improve management efficiency in one organization, enhance supply chain coordination, and attract investment, etc. Powerful as bigdata and AI technology, they cannot operate without data. In centralized, third-party-managed IIoT platform, few manufactures are willing to share their critical data. This study extends IIoT framework with blockchain technology to provide a solution for trustless data sharing. The solution embeds encrypted ledger to avoid credential data tampering, employs m-in-n-out smart contracts to secure data exchange, and utilizes consensus mechanism to improve cyber security. The proposed framework integrates blockchain with IIoT to operate the entire industrial data exchange in a decentralized network, namely Industrial Blockchain of Things (IBoT).","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114392894","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: 12

Simultaneous Planning of Grasp and Motion using Sample Regions and Gradient-Based Optimization 基于样本区域和梯度优化的抓取和运动同步规划

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9217027

Takayuki Murooka, A. I. Károly, Felix von Drigalski, Yoshihisa Ijiri

{"title":"Simultaneous Planning of Grasp and Motion using Sample Regions and Gradient-Based Optimization","authors":"Takayuki Murooka, A. I. Károly, Felix von Drigalski, Yoshihisa Ijiri","doi":"10.1109/CASE48305.2020.9217027","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9217027","url":null,"abstract":"Motion planning is an essential component of robotic systems. Gradient-based planning has been proposed to produce smooth paths under constraints for manipulation tasks such as picking and placing objects. However, it does not deal well with discontinuities, which occur in many manipulation problems, e.g. when deciding whether to pick an object from the side or from the top. Sampling-based planning is robust against such discontinuities, but often produces paths with unnecessary motions that require heavy post-processing. In this paper, we propose a novel method to solve a complete manipulation task using gradient-based optimization while preserving the advantages of sampling-based planning. By dividing the surface of the object into regions where the grasp pose can be extracted quasi-continuously, we define multiple optimization problems in parallel, which are evaluated independently. As our method generates the motion path and grasp plan for the entire task, constraints that arise from each moment of the task are propagated automatically to the optimization of the entire task, facilitating the setup. We show the effectiveness of the proposed method in simulation and with a real robot.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114806718","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

A Genetic Programming-Based Evolutionary Approach for Flexible Job Shop Scheduling with Multiple Process Plans 基于遗传规划的多工序柔性作业车间调度进化方法

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216783

Xuedong Zhu, Weihao Wang, Xinxing Guo, Leyuan Shi

引用次数: 5

Reactive grasping using high-resolution tactile sensors 使用高分辨率触觉传感器的反应抓取

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9217038

Reem Muhammed Al-Gaifi, Veit Müller, N. Elkmann

引用次数: 2

A data-driven exact algorithm for the container relocation problem 一种数据驱动的精确集装箱重定位算法

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216846

Canrong Zhang, Hao Guan

引用次数: 2

Robotic Pick-and-Toss Facilitates Urban Waste Sorting * 机器人拾取和投掷方便城市垃圾分类*

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216746

Fredy Raptopoulos, Maria Koskinopoulou, M. Maniadakis

引用次数: 15

Fault detection for autonomous multirotors using a redundant flight control architecture 基于冗余飞行控制体系的自主多旋翼故障检测

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216786

M. Lieret, Jonas Fertsch, J. Franke

{"title":"Fault detection for autonomous multirotors using a redundant flight control architecture","authors":"M. Lieret, Jonas Fertsch, J. Franke","doi":"10.1109/CASE48305.2020.9216786","DOIUrl":"https://doi.org/10.1109/CASE48305.2020.9216786","url":null,"abstract":"Within the last years unmanned aerial vehicles (UAV) have found their way into several industrial applications and are currently considered to be a highly efficient solution to deliver parcels to end costumers. However, a power shutdown or emergency stop of the propulsion system in the case of a failure is compared to stationary or mobile ground robots no suitable reaction as it leads to a fall of the UAV and hence creates a safety hazard for persons in the surroundings. Thus it must be ensured that the UAV is not only capable of detecting occurring failures but also of remaining airworthy and navigable at any time.Within this work we therefore present a fault detection approach for autonomous multirotor systems using a redundant flight control architecture. The presented fault detection methodology is capable of analysing flight control units (FCU) based on different hard- and software and does not require a precise time synchronization. To deal with different and unsynchronized FCUs we design and implement an inexact voter to continuously compare states and functionalities of the individual FCUs. In the case of a failure or break down of the active FCU the developed architecture has the ability of switching to one of the fallback systems.The approach and algorithms used for failure detection are presented in detail and afterwards the overall system is evaluated using a hexarotor in different flight states and conditions.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"T156 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125658902","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: 2

Learning Multi-Agent Communication with Policy Fingerprints for Adaptive Traffic Signal Control 基于策略指纹学习的多智能体通信自适应交通信号控制

2020 IEEE 16th International Conference on Automation Science and Engineering (CASE) Pub Date : 2020-08-01 DOI: 10.1109/CASE48305.2020.9216981

Yifan Zhao, Gangyan Xu, Yali Du, Meng Fang

引用次数: 2