2022 30th Mediterranean Conference on Control and Automation (MED)最新文献_第6页

Dominant modes estimation using SCUSUM method along with SSI 利用SCUSUM方法和SSI方法进行优势模态估计

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837208

V. ShashankS., M. R. Mariya, M. Mamta

引用次数: 0

Finite Frequency H∞ Control of Two-Dimensional Continuous Takagi-Sugeno Systems 二维连续Takagi-Sugeno系统的有限频率H∞控制

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837251

I. Rachid, T. Zoulagh, F. Tadeo, Hassnae Merzouki, E. Tissir

引用次数: 1

Precise Motion Control of Autonomous Robots 自主机器人的精确运动控制

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837200

B. Novakovic, D. Majetic, J. Kasać, D. Brezak

引用次数: 0

RRT-based Path Planning for Car-Like Vehicles with Nonholonomic Constraints 非完整约束下基于rrt的类车路径规划

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837136

Sotirios Spanogianopoulos, K. Sirlantzis, Kenan Ahiska

引用次数: 1

A Hierarchical Dual Decomposition-based Distributed Optimization Algorithm combining Quasi-Newton Steps and Bundle Methods 结合准牛顿步法和束法的分层对偶分布优化算法

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837219

V. Yfantis, M. Ruskowski

引用次数: 1

Optimal MmWave Sensor Selection for Bearing-Only Localization in Smart Environments 智能环境下纯方位定位的毫米波传感器优化选择

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837261

Evangelos Vlachos, E. Spyrou, C. Stylios, K. Berberidis

引用次数: 0

SLAM and Map Learning using Hybrid Semantic Graph Optimization * 基于混合语义图优化的SLAM和地图学习*

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837164

A. Agrawal, Dhruv Agarwal, Mehul Arora, Ritik Mahajan, Shivansh Beohar, Lhilo Kenye, R. Kala

{"title":"SLAM and Map Learning using Hybrid Semantic Graph Optimization *","authors":"A. Agrawal, Dhruv Agarwal, Mehul Arora, Ritik Mahajan, Shivansh Beohar, Lhilo Kenye, R. Kala","doi":"10.1109/MED54222.2022.9837164","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837164","url":null,"abstract":"Visual Simultaneous Localization and Mapping using budget-grade cameras only faces the challenges of continuous drifts that accumulate with time. While loop closure techniques mitigate the effects, they are applicable only when the robot completes a loop, which is a rarity in everyday navigation. The motion blur and smaller resolution of budget cameras further reduce the accuracy of SLAM. In this paper, we aim to solve the problem of active drift correction for a low-cost robot to solve autonomous navigation using the semantic map. Semantic maps have been used previously for re-localization but are useful only when the semantic maps themselves are highly accurate which is not realizable for budget robots. The semantic maps also face problems of correspondence matching in areas rich with recurrent semantics. To alleviate the same effects, the robot performs SLAM using a hybrid graph optimization consisting of semantic points whose pose is obtained from the semantic map database, and the non-semantic point features. The semantic map corrects for the drift, while the non-semantic features apply local smoothing that helps in mitigating the errors of the semantic map. They also apply robustness against errors in correspondence matching. The semantic graph may itself have errors, which are hence learned with time as the robot navigates. The robot adds new semantic objects into the database if it observes them, while the robot also mends the position based on the new observations. The initial semantic map is made using images captured by a camera on a few known poses, based on which it adds the observed semantics.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116950419","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

Edge Computing Architectures for Enabling the Realisation of the Next Generation Robotic Systems 实现下一代机器人系统的边缘计算架构

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837289

Achilleas Santi Seisa, Gerasimos Damigos, S. Satpute, A. Koval, G. Nikolakopoulos

{"title":"Edge Computing Architectures for Enabling the Realisation of the Next Generation Robotic Systems","authors":"Achilleas Santi Seisa, Gerasimos Damigos, S. Satpute, A. Koval, G. Nikolakopoulos","doi":"10.1109/MED54222.2022.9837289","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837289","url":null,"abstract":"Edge Computing is a promising technology to provide new capabilities in technological fields that require instantaneous data processing. Researchers in areas such as machine and deep learning use extensively edge and cloud computing for their applications, mainly due to the significant computational and storage resources that they provide. Currently, Robotics is seeking to take advantage of these capabilities as well, and with the development of 5G networks, some existing limitations in the field can be overcome. In this context, it is important to know how to utilize the emerging edge architectures, what types of edge architectures and platforms exist today and which of them can and should be used based on each robotic application. In general, Edge platforms can be implemented and used differently, especially since there are several providers offering more or less the same set of services with some essential differences. Thus, this study addresses these discussions for those who work in the development of the next generation robotic systems and will help to understand the advantages and disadvantages of each edge computing architecture in order to choose wisely the right one for each application.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131230088","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: 5

Attack-Resilient Multi-Agent Flocking Control Using Graph Neural Networks 基于图神经网络的攻击弹性多智能体群集控制

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837237

C. Bhowmick, Mudassir Shabbir, X. Koutsoukos

{"title":"Attack-Resilient Multi-Agent Flocking Control Using Graph Neural Networks","authors":"C. Bhowmick, Mudassir Shabbir, X. Koutsoukos","doi":"10.1109/MED54222.2022.9837237","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837237","url":null,"abstract":"Flocking control of a group of mobile agents has been recently investigated using Graph Convolution Networks (GCNs). The design relies on training using a centralized controller but the resulting GCN controller is based on communication between the agents. The agents receive sensor measurements which are incorporated into the states and shared between the neighbors. However, the paradigm is prone to adversarial attacks. In this paper, we consider the problem of designing GCN-based distributed flocking control that is resilient to attacks on the communicated information. We consider an attack model that is used to compromise the inter-agent communication and may inject arbitrary signals. Our control design uses a coordinate-wise median-based aggregation function. It is shown that the GCN-based controller using the proposed aggregation method is resilient against attacks on the communication between the agents, whereas the typical average-based aggregation fails to maintain the flock structure. Robustness analysis is performed to show that the proposed method is resilient whenever a majority of the agents in the neighborhood can be trusted. Simulation results and analysis are presented that validate the merits of the proposed approach.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131334551","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

PWA-CTM: An Extended Cell-Transmission Model based on Piecewise Affine Approximation of the Fundamental Diagram 基于基本图分段仿射逼近的扩展蜂窝传输模型PWA-CTM

2022 30th Mediterranean Conference on Control and Automation (MED) Pub Date : 2022-06-28 DOI: 10.1109/MED54222.2022.9837131

F. Alimardani, J. Baras

{"title":"PWA-CTM: An Extended Cell-Transmission Model based on Piecewise Affine Approximation of the Fundamental Diagram","authors":"F. Alimardani, J. Baras","doi":"10.1109/MED54222.2022.9837131","DOIUrl":"https://doi.org/10.1109/MED54222.2022.9837131","url":null,"abstract":"Throughout the past decades, many different versions of the widely used first-order Cell-Transmission Model (CTM) have been proposed for optimal traffic control. Highway traffic management techniques such as Ramp Metering (RM) are typically designed based on an optimization problem with nonlinear constraints originating in the flow-density relation of the Fundamental Diagram (FD). Most of the extended CTM versions are based on the trapezoidal approximation of the flow-density relation of the Fundamental Diagram (FD) in an attempt to simplify the optimization problem. However, this relation is naturally nonlinear, and crude approximations can greatly impact the efficiency of the optimization solution. In this study, we propose a class of extended CTMs that are based on piecewise affine approximations of the flow-density relation such that (a) the integrated squared error with respect to the true relation is greatly reduced in comparison to the trapezoidal approximation, and (b) the optimization problem remains tractable for real-time application of ramp metering optimal controllers. A two-step identification method is used to approximate the FD with piecewise affine functions resulting in what we refer to as PWA-CTMs. The proposed models are evaluated by the performance of the optimal ramp metering controllers, e.g. using the widely used PI-ALINEA approach, in complex highway traffic networks. Simulation results show that the optimization problems based on the PWA-CTMs require less computation time compared to other CTM extensions while achieving higher accuracy of the flow and density evolution. Hence, the proposed PWA-CTMs constitute one of the best approximation approaches for first-order traffic flow models that can be used in more general and challenging modeling and control applications.","PeriodicalId":354557,"journal":{"name":"2022 30th Mediterranean Conference on Control and Automation (MED)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132234245","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