2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)最新文献_第2页

Leveraging Edge Computing and Differential Privacy to Securely Enable Industrial Cloud Collaboration Along the Value Chain 利用边缘计算和差分隐私，在价值链上安全地实现工业云协作

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551656

Alexander Giehl, Michael P. Heinl, Maximilian Busch

引用次数: 0

Model predictive control based algorithm for multi-target tracking using a swarm of fixed wing UAVs 基于模型预测控制的固定翼无人机多目标跟踪算法

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551577

Animesh Sahu, Harikumar Kandath, K. Krishna

{"title":"Model predictive control based algorithm for multi-target tracking using a swarm of fixed wing UAVs","authors":"Animesh Sahu, Harikumar Kandath, K. Krishna","doi":"10.1109/CASE49439.2021.9551577","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551577","url":null,"abstract":"This paper presents a model predictive control (MPC) based algorithm for tracking multiple targets using a swarm of unmanned aerial vehicles (UAVs). All the UAVs belong to fixed-wing category with constraints on flight velocity, climb rate and turn rate. Each UAV carries a camera to detect and track the target. Two cases are considered where for the first case, the number of the UAVs is equal to the number of targets. For the second case, the number of UAVs is lesser than the number of targets leading to a conservative solution where the objective is to maximize the average time duration for which the targets are in the field-of-view (FOV) of any one of the UAV's camera. A data driven Gaussian process (GP) based model is developed to relate the hyperparameters used in MPC to the mission efficiency. Bayesian optimization is performed to obtain the hyperparameters of the MPC that maximize the mission efficiency. Numerical simulations are performed for both cases using algorithm based on distributed MPC formulation. A performance comparison is provided with the centralized MPC formulation.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"170 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122786181","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

Smooth Static Walking for Quadruped Robots based on the Lemniscate of Gerono 基于Gerono Lemniscate的四足机器人平滑静态行走

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551461

Xiaolong Ma, Linqi Ye, Houde Liu, Xueqian Wang, Bin Liang

{"title":"Smooth Static Walking for Quadruped Robots based on the Lemniscate of Gerono","authors":"Xiaolong Ma, Linqi Ye, Houde Liu, Xueqian Wang, Bin Liang","doi":"10.1109/CASE49439.2021.9551461","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551461","url":null,"abstract":"In the research of quadruped robots, stability is a very important consideration for gait design. When the robots have symmetrical structure, stability can be easily guaranteed. However, when the robots are carrying some additional devices or payloads unevenly, the position of the center of gravity (COG) may deviate from the geometrical center, which makes it a challenging task to guarantee stability. To handle this, it is of great significance to improve the stability margin during gait design. To this end, a smooth static walking gait with the maximum stability margin is developed in this paper. An algorithm of COG trajectory optimization based on the lemniscate of Gerono is proposed. The advantage of this algorithm is that the COG trajectory is smooth and continuous at any order, which avoids abrupt changes in velocity or acceleration of the robot during walking. The two parameters in the lemniscate are the main tuning parameters. According to the size of the robot, the algorithm can automatically calculate the optimal parameters (adjust the shape of the Gerono lemniscate curve) and balance the relationship between the step size and the stability margin during the robot movement. Simulation results demonstrate the effectiveness of the proposed method, and we use a mass block experiment to prove the insensitivity of the gait algorithm to the position of the COG.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122821673","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

Manufacturing Line Design Configuration with Optimized Resource Groups 优化资源组的生产线设计配置

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551650

T. Nakano, Kajita Daiki, Heming Chen, Ilya Kovalenko, Efe C. Balta, Yassine Qamsane, K. Barton

{"title":"Manufacturing Line Design Configuration with Optimized Resource Groups","authors":"T. Nakano, Kajita Daiki, Heming Chen, Ilya Kovalenko, Efe C. Balta, Yassine Qamsane, K. Barton","doi":"10.1109/CASE49439.2021.9551650","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551650","url":null,"abstract":"This research aims to develop methods to quickly build new manufacturing lines in response to changes in product varieties and manufacturing fluctuations in a factory. We propose a meta-heuristic algorithm for solving large-scale optimizations of the line design process, which includes resource configuration, process design, control design, and line configuration. The proposed framework improves the automation and system-level interactions of the line design process as compared to conventional methods that manually solve each step in the process design problem individually using skilled line engineers with previous experience. This research introduces the concept of a resource group or module that consists of various manufacturing resources such as robots, tools, autonomous guided vehicles, and conveyors. The line design process is then reconfigured for module or group configuration. To demonstrate the proposed framework, a case study is conducted in which the proposed framework is applied to the line design of an assembly manufacturing facility with production costs and manufacturing lead times selected as the key performance indicators of interest. Results indicate improved line costs and manufacturing lead times concurrently.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114445759","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

Sparse Multi-sensor Monitoring System Design for Vehicle Application 稀疏多传感器车载监控系统设计

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551647

Saeideh Khatiry Goharoodi, T. Ooijevaar, A. Bey-Temsamani, G. Crevecoeur

{"title":"Sparse Multi-sensor Monitoring System Design for Vehicle Application","authors":"Saeideh Khatiry Goharoodi, T. Ooijevaar, A. Bey-Temsamani, G. Crevecoeur","doi":"10.1109/CASE49439.2021.9551647","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551647","url":null,"abstract":"In today's fast growing vehicle industry, the number of functionalities (comfort features, monitoring features, safety features, etc.) is steadily increasing. Each of these functionalities are developed independently from each other, hence the sensors are not shared among them. Although this design approach results into robust monitoring of these different functionalities, it requires a large number of sensors in different locations resulting in a complex hardware and software architecture (e.g. complex wires). This paper describes our approach where a multi sensor design method is used to optimally select locations of sensors that are shared by different functionalities. This results into a reduced number of sensors that monitor the same amount of functionalities. We demonstrate in this paper, an optimization algorithm based on Multi-Objective Integer Programming (MOIP) for optimal sensor placement for monitoring Motion Sickness Dose Value (MSDV) estimation and Speed Bump Detection (SBD) as part of a driver assistant system. The algorithm is further validated on a numerical data-set captured from an IPG CarMaker vehicle model. The methodology can be further extended to more functionalities with large number of applications in vehicle industry.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117038451","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

Supervised Classification with Short-Term Memory of Sleep Stages using Cardio-respiratory and Body Movement Variables 使用心肺和身体运动变量对睡眠阶段短期记忆进行监督分类

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551493

Asma Gasmi, V. Augusto, Paul-Antoine Beaudet, J. Faucheu, C. Morin, Xavier Serpaggi, F. Vassel

引用次数: 0

The Just-In-Time Job-Shop Rescheduling with Rush Orders by Using a Meta-Heuristic Algorithm 基于元启发式算法的急单作业车间准时调度

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551573

Xiyue Ren, Xiuxian Wang, Na Geng, Zhibin Jiang

引用次数: 0

Configuration Estimation of Continuum Robots Using Piecewise Constant Curvature Generalized Epi-Polar Constraint Model 基于分段常曲率广义外极约束模型的连续统机器人构型估计

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551587

Hao Cheng, Houde Liu, Xueqian Wang, Bin Liang

{"title":"Configuration Estimation of Continuum Robots Using Piecewise Constant Curvature Generalized Epi-Polar Constraint Model","authors":"Hao Cheng, Houde Liu, Xueqian Wang, Bin Liang","doi":"10.1109/CASE49439.2021.9551587","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551587","url":null,"abstract":"In recent years, continuum robots have attracted more attention for they can work in more severe environments. However, at present, most of the research focuses on the mechanical structure innovation, and there are few pieces of research on the control of this kind of robot. Since continuum robots are deformable, their shape is a general curve in space. Therefore, they are not fully defined by actuator positions, which are different from the traditional rigid robots. To achieve more accurate control, a method of sensing robot configuration in real-time is necessary. However, the existing visual-based approaches all adopt external global cameras, which is difficult to adapt to the demand of unknown unstructured environments. This paper presents a system capable of estimating the configuration of continuum robots under piecewise constant curvature (PCC) assumption from cameras mounted on each constant curvature segment. Specifically, we first proposed the PCC 2R model, which is equivalent to each cc-segment of PCC continuum robots by two joints rigid bodies, thereby reducing the problem complexity and improving the numerical stability of the estimation. Then, based on the PCC 2R model, we proposed the PCC generalized epi-polar constraint to completely constrain the four degrees of freedom of each cc-segment in planar, it can be solved through one corresponds, to estimate the configuration of continuum robots under PCC. Finally, the above approach is verified by experiment.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127037840","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

Incorporating Generalized Momentum Method to Accelerate Clustering Analysis of Complex Networks 基于广义动量法的复杂网络聚类分析

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551512

Lun Hu, Xiangyu Pan, Xin Luo

引用次数: 1

A Data-Driven Multi-Device Collaborative Control Method in Coal Transportation System 煤炭运输系统中数据驱动的多设备协同控制方法

2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) Pub Date : 2021-08-23 DOI: 10.1109/CASE49439.2021.9551531

Bo You, Liu Kang, Shuaishuai Wang, Xueen Li

{"title":"A Data-Driven Multi-Device Collaborative Control Method in Coal Transportation System","authors":"Bo You, Liu Kang, Shuaishuai Wang, Xueen Li","doi":"10.1109/CASE49439.2021.9551531","DOIUrl":"https://doi.org/10.1109/CASE49439.2021.9551531","url":null,"abstract":"The coal transportation system comprises several belt conveyors, which includes lots of electrical equipment. The devices are interconnected, and a problem with one of them will cause all devices to be paralyzed. So rapid and accurate multi-device collaborative control plays an important role in high safety performance and production efficiency. Traditional multi-device collaborative control algorithms depend on complex modeling with large-scale, complex constraints, uncertainties, and multi-objective conditions. Here, we propose a data-driven multi-device collaborative control method. In this paper, the neural network algorithm is selected to model the relationship between the equipment control operation and the environment, equipment status, and human activities, thus forming the multi-device collaborative control operation knowledge to guide the multi-device collaborative control in the actual operation process. Furthermore, experiments on real production datasets demonstrate the proposed approach can realize multi-device collaborative control in the coal transportation system, meeting the three goals of safety, energy-saving, and high efficiency simultaneously.","PeriodicalId":232083,"journal":{"name":"2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121168233","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