IET Cybersystems and Robotics最新文献

Anti-sloshing control: Flatness-based trajectory planning and tracking control with an integrated extended state observer 防滑控制：基于平整度的轨迹规划和跟踪控制与综合扩展状态观测器

IF 1.5

IET Cybersystems and Robotics Pub Date : 2024-08-25 DOI: 10.1049/csy2.12121

Khanh Nguyen Viet, Minh Do Duc, Thanh Cao Duc, Tung Lam Nguyen

引用次数: 0

Multi-feature fusion and memory-based mobile robot target tracking system 基于多特征融合和记忆的移动机器人目标跟踪系统

IF 1.5

IET Cybersystems and Robotics Pub Date : 2024-07-17 DOI: 10.1049/csy2.12119

Hanqing Sun, Shijie Zhang, Qingle Quan

引用次数: 0

Internal and external disturbances aware motion planning and control for quadrotors 内部和外部干扰感知四旋翼飞行器的运动规划和控制

IF 1.5

IET Cybersystems and Robotics Pub Date : 2024-07-17 DOI: 10.1049/csy2.12122

Xiaobin Zhou, Miao Wang, Can Cui, Yongchao Wang, Chao Xu, Fei Gao

{"title":"Internal and external disturbances aware motion planning and control for quadrotors","authors":"Xiaobin Zhou, Miao Wang, Can Cui, Yongchao Wang, Chao Xu, Fei Gao","doi":"10.1049/csy2.12122","DOIUrl":"https://doi.org/10.1049/csy2.12122","url":null,"abstract":"Resilient motion planning and control, without prior knowledge of disturbances, are crucial to ensure the safe and robust flight of quadrotors. The development of a motion planning and control architecture for quadrotors, considering both internal and external disturbances (i.e., motor damages and suspended payloads), is addressed. Firstly, the authors introduce the use of exponential functions to formulate trajectory planning. This choice is driven by its ability to predict thrust responses with minimal computational overhead. Additionally, a reachability analysis is incorporated for error dynamics resulting from multiple disturbances. This analysis sits at the interface between the planner and controller, contributing to the generation of more robust and safe spatial–temporal trajectories. Lastly, the authors employ a cascade controller, with the assistance of internal and external loop observers, to further enhance resilience and compensate the disturbances. The authors’ benchmark experiments demonstrate the effectiveness of the proposed strategy in enhancing flight safety, particularly when confronted with motor damages and payload disturbances.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.12122","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141639531","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

Efficient knowledge distillation for hybrid models: A vision transformer-convolutional neural network to convolutional neural network approach for classifying remote sensing images 混合模型的高效知识提炼：用于遥感图像分类的视觉转换器-卷积神经网络-卷积神经网络方法

IF 1.5

IET Cybersystems and Robotics Pub Date : 2024-07-10 DOI: 10.1049/csy2.12120

Huaxiang Song, Yuxuan Yuan, Zhiwei Ouyang, Yu Yang, Hui Xiang

{"title":"Efficient knowledge distillation for hybrid models: A vision transformer-convolutional neural network to convolutional neural network approach for classifying remote sensing images","authors":"Huaxiang Song, Yuxuan Yuan, Zhiwei Ouyang, Yu Yang, Hui Xiang","doi":"10.1049/csy2.12120","DOIUrl":"https://doi.org/10.1049/csy2.12120","url":null,"abstract":"In various fields, knowledge distillation (KD) techniques that combine vision transformers (ViTs) and convolutional neural networks (CNNs) as a hybrid teacher have shown remarkable results in classification. However, in the realm of remote sensing images (RSIs), existing KD research studies are not only scarce but also lack competitiveness. This issue significantly impedes the deployment of the notable advantages of ViTs and CNNs. To tackle this, the authors introduce a novel hybrid-model KD approach named HMKD-Net, which comprises a CNN-ViT ensemble teacher and a CNN student. Contrary to popular opinion, the authors posit that the sparsity in RSI data distribution limits the effectiveness and efficiency of hybrid-model knowledge transfer. As a solution, a simple yet innovative method to handle variances during the KD phase is suggested, leading to substantial enhancements in the effectiveness and efficiency of hybrid knowledge transfer. The authors assessed the performance of HMKD-Net on three RSI datasets. The findings indicate that HMKD-Net significantly outperforms other cutting-edge methods while maintaining a significantly smaller size. Specifically, HMKD-Net exceeds other KD-based methods with a maximum accuracy improvement of 22.8% across various datasets. As ablation experiments indicated, HMKD-Net has cut down on time expenses by about 80% in the KD process. This research study validates that the hybrid-model KD technique can be more effective and efficient if the data distribution sparsity in RSIs is well handled.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.12120","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597026","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

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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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":null,"pages":null},"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