IET Cybersystems and Robotics最新文献_第2页

FlockSeer: A portable stereo vision observer for bird flocking FlockSeer：用于鸟群的便携式立体视觉观测器

IF 1.5

IET Cybersystems and Robotics Pub Date : 2024-06-26 DOI: 10.1049/csy2.12118

Yuhui Ai, Haozhou Zhai, Zijie Sun, Weiming Yan, Tianjiang Hu

{"title":"FlockSeer: A portable stereo vision observer for bird flocking","authors":"Yuhui Ai, Haozhou Zhai, Zijie Sun, Weiming Yan, Tianjiang Hu","doi":"10.1049/csy2.12118","DOIUrl":"https://doi.org/10.1049/csy2.12118","url":null,"abstract":"Bird flocking is a paradigmatic case of self-organised collective behaviours in biology. Stereo camera systems are employed to observe flocks of starlings, jackdaws, and chimney swifts, mainly on a spot-fixed basis. A portable non-fixed stereo vision-based flocking observation system, namely FlockSeer, is developed by the authors for observing more species of bird flocks within field scenarios. The portable flocking observer, FlockSeer, responds to the challenges in extrinsic calibration, camera synchronisation and field movability compared to existing spot-fixed observing systems. A measurement and sensor fusion approach is utilised for rapid calibration, and a light-based synchronisation approach is used to simplify hardware configuration. FlockSeer has been implemented and tested across six cities in three provinces and has accomplished diverse flock-tracking tasks, accumulating behavioural data of four species, including egrets, with up to 300 resolvable trajectories. The authors reconstructed the trajectories of a flock of egrets under disturbed conditions to verify the practicality and reliability. In addition, we analysed the accuracy of identifying nearest neighbours, and then examined the similarity between the trajectories and the Couzin model. Experimental results demonstrate that the developed flocking observing system is highly portable, more convenient and swift to deploy in wetland-like or coast-like fields. Its observation process is reliable and practical and can effectively support the study of understanding and modelling of bird flocking behaviours.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"6 3","pages":""},"PeriodicalIF":1.5,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.12118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141488188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated federated learning-based adversarial attack and defence in industrial control systems 工业控制系统中基于联合学习的自动对抗攻防

IET Cybersystems and Robotics Pub Date : 2024-05-31 DOI: 10.1049/csy2.12117

Guo-Qiang Zeng, Jun-Min Shao, Kang-Di Lu, Guang-Gang Geng, Jian Weng

{"title":"Automated federated learning-based adversarial attack and defence in industrial control systems","authors":"Guo-Qiang Zeng, Jun-Min Shao, Kang-Di Lu, Guang-Gang Geng, Jian Weng","doi":"10.1049/csy2.12117","DOIUrl":"https://doi.org/10.1049/csy2.12117","url":null,"abstract":"With the development of deep learning and federated learning (FL), federated intrusion detection systems (IDSs) based on deep learning have played a significant role in securing industrial control systems (ICSs). However, adversarial attacks on ICSs may compromise the ability of deep learning-based IDSs to accurately detect cyberattacks, leading to serious consequences. Moreover, in the process of generating adversarial samples, the selection of replacement models lacks an effective method, which may not fully expose the vulnerabilities of the models. The authors first propose an automated FL-based method to generate adversarial samples in ICSs, called AFL-GAS, which uses the principle of transfer attack and fully considers the importance of replacement models during the process of adversarial sample generation. In the proposed AFL-GAS method, a lightweight neural architecture search method is developed to find the optimised replacement model composed of a combination of four lightweight basic blocks. Then, to enhance the adversarial robustness, the authors propose a multi-objective neural architecture search-based IDS method against adversarial attacks in ICSs, called MoNAS-IDSAA, by considering both classification performance on regular samples and adversarial robustness simultaneously. The experimental results on three widely used intrusion detection datasets in ICSs, such as secure water treatment (SWaT), Water Distribution, and Power System Attack, demonstrate that the proposed AFL-GAS method has obvious advantages in evasion rate and lightweight compared with other four methods. Besides, the proposed MoNAS-IDSAA method not only has a better classification performance, but also has obvious advantages in model adversarial robustness compared with one manually designed federated adversarial learning-based IDS method.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"6 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.12117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141187557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ER-Mapping: An extrinsic robust coloured mapping system using residual evaluation and selection ER-Mapping：使用残差评估和选择的外在稳健彩色绘图系统

IET Cybersystems and Robotics Pub Date : 2024-05-23 DOI: 10.1049/csy2.12116

Changjian Jiang, Zeyu Wan, Ruilan Gao, Yu Zhang

引用次数: 0

ATI: Assemble topological interaction overcomes consistency–cohesion trade-off in bird flocking ATI：集合拓扑相互作用克服了鸟群中一致性与内聚性的权衡

IET Cybersystems and Robotics Pub Date : 2024-04-21 DOI: 10.1049/csy2.12114

Jialei Huang, Bo Zhu, Tianjiang Hu

{"title":"ATI: Assemble topological interaction overcomes consistency–cohesion trade-off in bird flocking","authors":"Jialei Huang, Bo Zhu, Tianjiang Hu","doi":"10.1049/csy2.12114","DOIUrl":"https://doi.org/10.1049/csy2.12114","url":null,"abstract":"In nature, various animal groups like bird flocks display proficient collective navigation achieved by maintaining high consistency and cohesion simultaneously. Both metric and topological interactions have been explored to ensure high consistency among groups. The topological interactions found in bird flocks are more cohesive than metric interactions against external perturbations, especially the spatially balanced topological interaction (SBTI). However, it is revealed that in complex environments, pursuing cohesion via existing interactions compromises consistency. The authors introduce an innovative solution, assemble topological interaction, to address this challenge. Contrasting with static interaction rules, the new interaction empowers individuals with self-awareness to adapt to the complex environment by switching between interactions through visual cues. Most individuals employ high-consistency k-nearest topological interaction when not facing splitting threats. In the presence of such threats, some switch to the high-cohesion SBTI to avert splitting. The assemble topological interaction thus transcends the limit of the trade-off between consistency and cohesion. In addition, by comparing groups with varying degrees of these two features, the authors demonstrate that group effects are vital for efficient navigation led by a minority of informed agents. Finally, the real-world drone-swarm experiments validate the applicability of the proposed interaction to artificial robotic collectives.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"6 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.12114","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140632031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recursive attention collaboration network for single image de-raining 用于单一图像去粒度的递归注意力协作网络

IET Cybersystems and Robotics Pub Date : 2024-04-17 DOI: 10.1049/csy2.12115

Zhitong Li, Xiaodong Li, Zhaozhe Gong, Zhensheng Yu

{"title":"Recursive attention collaboration network for single image de-raining","authors":"Zhitong Li, Xiaodong Li, Zhaozhe Gong, Zhensheng Yu","doi":"10.1049/csy2.12115","DOIUrl":"https://doi.org/10.1049/csy2.12115","url":null,"abstract":"Single-image rain removal is an important problem in the field of computer vision aimed at recovering clean images from rainy images. In recent years, data-driven convolutional neural network (CNN)-based rain removal methods have achieved significant results, but most of them cannot fully focus on the contextual information in rain-containing images, which leads to the failure of recovering some of the background details of the images that have been corrupted due to the aggregation of rain streaks. With the success of Transformer-based models in the field of computer vision, global features can be easily acquired to better help recover details in the background of an image. However, Transformer-based models often require a large number of parameters during the training process, which makes the training process very difficult and makes it difficult to apply them to specific devices for execution in reality. The authors propose a Recursive Attention Collaboration Network, which consists of a recursive Swin-transformer block (STB) and a CNN-based feature fusion block. The authors designed the Recursively Integrate Transformer Block (RITB), which consists of several STBs recursively connected, that can effectively reduce the number of parameters of the model. The final part of the module can integrate the local information from the STBs. The authors also design the Feature Enhancement Block, which can better recover the details of the background information corrupted by rain streaks of different density shapes through the features passed from the RITB. Experiments show that the proposed network has an effective rain removal effect on both synthetic and real datasets and has fewer model parameters than other mainstream methods.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"6 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.12115","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140606256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning to bag with a simulation-free reinforcement learning framework for robots 用机器人的无模拟强化学习框架学会装袋

IET Cybersystems and Robotics Pub Date : 2024-04-11 DOI: 10.1049/csy2.12113

Francisco Munguia-Galeano, Jihong Zhu, Juan David Hernández, Ze Ji

引用次数: 0

Distributed field mapping for mobile sensor teams using a derivative-free optimisation algorithm 使用无导数优化算法为移动传感器团队进行分布式实地测绘

IET Cybersystems and Robotics Pub Date : 2024-03-31 DOI: 10.1049/csy2.12111

Tony X. Lin, Jia Guo, Said Al-Abri, Fumin Zhang

引用次数: 0

ROSIC: Enhancing secure and accessible robot control through open-source instant messaging platforms ROSIC：通过开源即时通讯平台加强机器人控制的安全性和可及性

IET Cybersystems and Robotics Pub Date : 2024-03-29 DOI: 10.1049/csy2.12112

Rasoul Sadeghian, Shahrooz Shahin, Sina Sareh

{"title":"ROSIC: Enhancing secure and accessible robot control through open-source instant messaging platforms","authors":"Rasoul Sadeghian, Shahrooz Shahin, Sina Sareh","doi":"10.1049/csy2.12112","DOIUrl":"https://doi.org/10.1049/csy2.12112","url":null,"abstract":"Ensuring secure communication and seamless accessibility remains a primary challenge in controlling robots remotely. The authors propose a novel approach that leverages open-source instant messaging platforms to overcome the complexities and reduce costs associated with implementing a secure and user-centred communication system for remote robot control named Robot Control System using Instant Communication (ROSIC). By leveraging features, such as real-time messaging, group chats, end-to-end encryption and cross-platform support inherent in the majority of instant messenger platforms, we have developed middleware that establishes a secure and efficient communication system over the Internet. By using instant messaging as the communication interface between users and robots, ROSIC caters to non-technical users, making it easier for them to control robots. The architecture of ROSIC enables various scenarios for robot control, including one user controlling multiple robots, multiple users controlling one robot, multiple robots controlled by multiple users, and one user controlling one robot. Furthermore, ROSIC facilitates the interaction of multiple robots, enabling them to interoperate and function collaboratively as a swarm system by providing a unified communication platform that allows for seamless exchange of data and commands. Telegram was specifically chosen as the instant messaging platform by the authors due to its open-source nature, robust encryption, compatibility across multiple platforms and interactive communication capabilities through channels and groups. Notably, the ROSIC is designed to communicate effectively with robot operating system (ROS)-based robots to enhance our ability to control them remotely.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"6 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.12112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140329018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital twin-based multi-objective autonomous vehicle navigation approach as applied in infrastructure construction 应用于基础设施建设的基于数字孪生的多目标自主车辆导航方法

IET Cybersystems and Robotics Pub Date : 2024-03-20 DOI: 10.1049/csy2.12110

Tingjun Lei, Timothy Sellers, Chaomin Luo, Lei Cao, Zhuming Bi

{"title":"Digital twin-based multi-objective autonomous vehicle navigation approach as applied in infrastructure construction","authors":"Tingjun Lei, Timothy Sellers, Chaomin Luo, Lei Cao, Zhuming Bi","doi":"10.1049/csy2.12110","DOIUrl":"https://doi.org/10.1049/csy2.12110","url":null,"abstract":"The widespread adoption of autonomous vehicles has generated considerable interest in their autonomous operation, with path planning emerging as a critical aspect. However, existing road infrastructure confronts challenges due to prolonged use and insufficient maintenance. Previous research on autonomous vehicle navigation has focused on determining the trajectory with the shortest distance, while neglecting road construction information, leading to potential time and energy inefficiencies in real-world scenarios involving infrastructure development. To address this issue, a digital twin-embedded multi-objective autonomous vehicle navigation is proposed under the condition of infrastructure construction. The authors propose an image processing algorithm that leverages captured images of the road construction environment to enable road extraction and modelling of the autonomous vehicle workspace. Additionally, a wavelet neural network is developed to predict real-time traffic flow, considering its inherent characteristics. Moreover, a multi-objective brainstorm optimisation (BSO)-based method for path planning is introduced, which optimises total time-cost and energy consumption objective functions. To ensure optimal trajectory planning during infrastructure construction, the algorithm incorporates a real-time updated digital twin throughout autonomous vehicle operations. The effectiveness and robustness of the proposed model are validated through simulation and comparative studies conducted in diverse scenarios involving road construction. The results highlight the improved performance and reliability of the autonomous vehicle system when equipped with the authors’ approach, demonstrating its potential for enhancing efficiency and minimising disruptions caused by road infrastructure development.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"6 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.12110","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140181594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An efficient and robust system for human following scenario using differential robot 利用差分机器人实现高效稳健的人类追随系统

IET Cybersystems and Robotics Pub Date : 2024-01-25 DOI: 10.1049/csy2.12108

Jiangchao Zhu, Changjia Ma, Chao Xu, Fei Gao

引用次数: 0