2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR)最新文献_第4页

Design of one degree of freedom rotating platform applied in leader-follower autonomous robot control 引导者-随从自主机器人控制中一自由度旋转平台的设计

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874308

W. Kowalczyk, Arpit Joon

引用次数: 1

Robust Control of a Duocopter by Discrete-Time Sliding Mode Techniques and an Extended Kalman Filter for Disturbance Compensation 基于离散时间滑模技术和扩展卡尔曼滤波的双旋翼飞行器鲁棒控制

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874290

H. Aschemann

引用次数: 0

A Note of A Legless Capsubot Robot Control 一种无腿胶囊机器人的控制方法

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874273

A. Babiarz

引用次数: 1

Modeling of thermal processes in the microcontroller system using fractional order transfer function 用分数阶传递函数对微控制器系统中的热过程进行建模

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874336

K. Oprzȩdkiewicz, M. Rosół

引用次数: 2

Benchmarking Nonlinear Model Predictive Control with Input Parameterizations 基于输入参数化的非线性模型预测控制基准

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874297

F. Fusco, Guillaume Allibert, Olivier Kermorgant, P. Martinet

引用次数: 0

Early Fusion Based CNN Architecture for Visual Servoing Systems 基于早期融合的CNN视觉伺服系统架构

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874328

Adrian-Paul Botezatu, L. Ferariu, A. Burlacu, Teodor-Andrei Sauciuc

{"title":"Early Fusion Based CNN Architecture for Visual Servoing Systems","authors":"Adrian-Paul Botezatu, L. Ferariu, A. Burlacu, Teodor-Andrei Sauciuc","doi":"10.1109/MMAR55195.2022.9874328","DOIUrl":"https://doi.org/10.1109/MMAR55195.2022.9874328","url":null,"abstract":"Visual feedback control refers to the usage of image data to design the motion of a robotic system. This type of problem is equivalent to generating linear and angular velocities that will drive a robotic systems from an initial image to target one. Classic visual servoing methods have disadvantages, such as high challenges on extracting and tracking visual features, regardless of the environmental conditions, and nonlinear dependencies regarding camera calibration. During the last years, these limitations have been alleviated by employing Convolutional Neural Networks (CNNs). The main goal of this work is to increase the performance of CNNs in visual feedback control expanding the neural input arrays with extra available data. For this, extra maps created via region-based segmentation are considered as input in an early fusion based architecture. These ready-to-use simplified descriptions of the initial and final layouts can help CNN understand the scenes, and compute accurate velocities. The role of the segmented maps is experimentally investigated on two different architectures that exemplify the suggested design idea. The results show that CNNs with input fusion offer a better approximation of the linear and angular velocities, and proper robustness to segmentation errors, as well.","PeriodicalId":169528,"journal":{"name":"2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129676761","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

Incident Management Process Model for Automotive CyberSafety Systems Using the Business Process Model and Notation 基于业务流程模型和符号的汽车网络安全系统事件管理流程模型

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874288

P. Piątek

{"title":"Incident Management Process Model for Automotive CyberSafety Systems Using the Business Process Model and Notation","authors":"P. Piątek","doi":"10.1109/MMAR55195.2022.9874288","DOIUrl":"https://doi.org/10.1109/MMAR55195.2022.9874288","url":null,"abstract":"The rise of vehicle connectivity and autonomy is predicted to amplify the impact of emerging cybersecurity risks during the entire product life cycle in the automotive sector. To address all aspects of vehicle safety, including functional safety, safety of intended functionality (SOTIF), and cybersecurity, efforts must be made to collaborate across these areas during the maintenance period for incidents handling as well. Currently, much emphasis is being placed on the Incident Monitoring Process, which focuses on cybersecurity concerns. To round out the picture, safety incidents should be also considered. As a result, the research intends to examine SOTIF -related incidents in addition to cybersecurity issues. Following that, the paper gives a full model of the CyberSafety Incident Monitoring Process, which includes all industry requirements for cybersecurity monitoring as well as SOTIF-related concerns. The paper presents the proposal of using Business Process Model and Notation (BPMN) to create a complete process model. The probable practical implementation of the CyberSafety Incident Monitoring Process Model is evaluated in the last part of the study based on the phantom attack scenario to test the idea with a real-world example. As a consequence, the strategy is accurate and fits the industry goal of merging safety and cybersecurity during the maintenance phase, which reduces the time and effort necessary for faster response to various vehicle risks when time is crucial. In future research, more emphasis should be made on combining numerous incident fields, which may have an impact on vehicle safety.","PeriodicalId":169528,"journal":{"name":"2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR)","volume":"208 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129420828","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

Two Points Classical Identification Methods on the Example of a Three-Tank Interacting and Non-Interacting System 三罐相互作用与非相互作用系统实例的两点经典辨识方法

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874335

Anna Czemplik, J. Jagodziński

引用次数: 0

Improving the detection of noisy labels in image datasets using modified Confidence Learning 利用改进的置信度学习改进图像数据集中噪声标签的检测

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874318

A. Popowicz, Krystian Radlak, S. Lasota, Karolina Szczepankiewicz, Michal Szczepankiewicz

引用次数: 0

New approach to functional safety work products for advanced automotive projects 先进汽车项目功能安全工作产品的新方法

2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR) Pub Date : 2022-08-22 DOI: 10.1109/MMAR55195.2022.9874338

Piotr Mydlowski, S. Moskwa

{"title":"New approach to functional safety work products for advanced automotive projects","authors":"Piotr Mydlowski, S. Moskwa","doi":"10.1109/MMAR55195.2022.9874338","DOIUrl":"https://doi.org/10.1109/MMAR55195.2022.9874338","url":null,"abstract":"The dynamically developing automotive industry poses increasing challenges to manufacturers due to the increasing complexity of electronic systems used in cars and high safety requirements. The ISO 26262 standard gives guidelines for project management in the field of functional safety. It included lists of work products, which usually prepare fundamental documents in the field of functional safety, such as development interface agreement or functional safety plan, etc.. The degree of implementation of the mentioned work products helps in the arguments about the ultimate safety of the product. ISO 26262 is a standard aimed at the possibility of its wide application (also for the simplest products), unfortunately for highly complex products such as integrated safety systems, such high-level work products can be too general without contributing key information at the start of the project. The article presents a list of additional, more precise work products dedicated specifically to highly advanced safety systems in automotive projects. It can be used at the request for quote stage when building documentation for functional safety. In addition, the list of work products listed and introduced to the additional process helps to determine the scope of responsibilities in the organization at the beginning of the project. Especially where the issues of functional safety and safety of the intended functionality are presented. This helps to avoid the risk of security liability gaps with potentially fatal consequences for the end-user.","PeriodicalId":169528,"journal":{"name":"2022 26th International Conference on Methods and Models in Automation and Robotics (MMAR)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116597760","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