Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)最新文献_第3页

Data-Driven Modeling and High-Precision Tracking Control of a Soft Continuum Manipulator: Enabling Robotic Sorting of Multiwire Cables 软连续机械手的数据驱动建模和高精度跟踪控制：实现多线电缆的机器人分类

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-09-09 DOI: 10.1002/aisy.202300827

Yuan Gao, Zhi Chen, Fangxun Zhong, Xiang Li, Yun-Hui Liu

{"title":"Data-Driven Modeling and High-Precision Tracking Control of a Soft Continuum Manipulator: Enabling Robotic Sorting of Multiwire Cables","authors":"Yuan Gao, Zhi Chen, Fangxun Zhong, Xiang Li, Yun-Hui Liu","doi":"10.1002/aisy.202300827","DOIUrl":"https://doi.org/10.1002/aisy.202300827","url":null,"abstract":"As a new class of robots, soft continuum manipulators have attracted attention due to their flexibility and compliance. However, these characteristics create challenges for precise modeling and control. This study proposes a hybrid offline and online data-driven scheme to achieve high-precision tracking control of a soft continuum manipulator. First, a novel multiscale deep neural network learns the manipulator model offline. Specifically, the feature fusion module extracts highly discriminative features and captures long-term dependencies from the temporal trajectory data. The self-attention module strengthens the ability to represent fusion features and enhances the model prediction accuracy. Then, the learnt model is updated using multisensor data online, and the proposed controller further compensates for the updated model and enhances the tracking accuracy in the movement stage. Finally, the experimental results demonstrate a significant improvement in motion accuracy under different trajectory-tracking scenarios (i.e., deviations of <1 mm in position and <0.8° in orientation). The example of the multiwire cable sorting proves the feasibility of the proposed scheme in high-precision industrial applications.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"6 10","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202300827","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443496","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

Multihead Attention U-Net for Magnetic Particle Imaging–Computed Tomography Image Segmentation 用于磁粉成像-计算机断层扫描图像分割的多头注意力 U-Net

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-09-09 DOI: 10.1002/aisy.202400007

Aniwat Juhong, Bo Li, Yifan Liu, Chia-Wei Yang, Cheng-You Yao, Dalen W. Agnew, Yu Leo Lei, Gary D. Luker, Harvey Bumpers, Xuefei Huang, Wibool Piyawattanametha, Zhen Qiu

{"title":"Multihead Attention U-Net for Magnetic Particle Imaging–Computed Tomography Image Segmentation","authors":"Aniwat Juhong, Bo Li, Yifan Liu, Chia-Wei Yang, Cheng-You Yao, Dalen W. Agnew, Yu Leo Lei, Gary D. Luker, Harvey Bumpers, Xuefei Huang, Wibool Piyawattanametha, Zhen Qiu","doi":"10.1002/aisy.202400007","DOIUrl":"https://doi.org/10.1002/aisy.202400007","url":null,"abstract":"Magnetic particle imaging (MPI) is an emerging noninvasive molecular imaging modality with high sensitivity and specificity, exceptional linear quantitative ability, and potential for successful applications in clinical settings. Computed tomography (CT) is typically combined with the MPI image to obtain more anatomical information. Herein, a deep learning-based approach for MPI-CT image segmentation is presented. The dataset utilized in training the proposed deep learning model is obtained from a transgenic mouse model of breast cancer following administration of indocyanine green (ICG)-conjugated superparamagnetic iron oxide nanoworms (NWs-ICG) as the tracer. The NWs-ICG particles progressively accumulate in tumors due to the enhanced permeability and retention (EPR) effect. The proposed deep learning model exploits the advantages of the multihead attention mechanism and the U-Net model to perform segmentation on the MPI-CT images, showing superb results. In addition, the model is characterized with a different number of attention heads to explore the optimal number for our custom MPI-CT dataset.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"6 10","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202400007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443498","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

Game Theoretic Non-cooperative Dynamic Target Tracking for Directional Sensing-Enabled Unmanned Aerial Vehicles 支持定向传感的无人飞行器的博弈论非合作动态目标跟踪

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-09-04 DOI: 10.1002/aisy.202300725

Peng Yi, Ge Jin, Wenyuan Wang

{"title":"Game Theoretic Non-cooperative Dynamic Target Tracking for Directional Sensing-Enabled Unmanned Aerial Vehicles","authors":"Peng Yi, Ge Jin, Wenyuan Wang","doi":"10.1002/aisy.202300725","DOIUrl":"https://doi.org/10.1002/aisy.202300725","url":null,"abstract":"In this article, a game theoretic non-cooperative dynamic target tracking algorithm that empowers defensive unmanned aerial vehicles (UAVs), with directional sensing capabilities to track and collect information on intrusive UAVs, is proposed. Specifically, defenders aim to maximize the collection of identity information from intruders possessing anti-tracking and evading capabilities, while simultaneously preventing their entry into protected areas. Game theory is employed to determine the optimal confrontation paths for defenders against the intruders. The probability perception model is utilized for evaluating the dynamic target tracking capability and designing a tracking merit function to assess tracking performance, taking into account both the target's position and the perception relative angle. Furthermore, considering the dynamic interactive behaviors between intruders and defenders, the iterative linear quadratic game (ILQG) algorithm is employed to solve the Nash equilibrium of the non-cooperative target tracking game. Through simulation experiments, the effectiveness of the proposed algorithm in accomplishing multi-agent dynamic target tracking tasks is demonstrated and the performance of the algorithm under varying parameters in the intruder's cost function is evaluated, which represent different intrusion intentions.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"6 10","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202300725","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443573","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

A Shared Control Method for Teleoperated Robot Using Artificial Potential Field 利用人工势场的遥控机器人共享控制方法

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-09-04 DOI: 10.1002/aisy.202300814

Wenlei Qin, He Zhang, Zhibin Fan, Yanhe Zhu, Jie Zhao

{"title":"A Shared Control Method for Teleoperated Robot Using Artificial Potential Field","authors":"Wenlei Qin, He Zhang, Zhibin Fan, Yanhe Zhu, Jie Zhao","doi":"10.1002/aisy.202300814","DOIUrl":"https://doi.org/10.1002/aisy.202300814","url":null,"abstract":"Retinal surgery requires enclosed spatial constraints to improve the safety and success of the surgery. Herein, a shared control method is proposed for master–slave robot systems, utilizing tubular guidance constraints based on a novel potential field function to optimize the commands of the surgeon. Within the tube, attractive constraints intensify with increasing task error and approach infinity at the boundary of the tube. This ensures that the surgery is confined within a closed tubular space. Haptic feedback provides force cues to inform the surgeon about the feasibility of the input commands. Theoretical derivations demonstrate that the entire closed-loop system is passive. Two simulation experiments are conducted on the ophthalmic surgery robot platform to evaluate the functionality of the proposed method. The experimental results indicate that translational errors are kept less than certain predefined values. Furthermore, the proposed method outperforms the comparison method in terms of task accuracy and efficiency.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"6 10","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202300814","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443571","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

Nonlinear Variation Decomposition of Neural Networks for Holistic Semiconductor Process Monitoring 用于整体半导体过程监控的神经网络非线性变化分解

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-09-04 DOI: 10.1002/aisy.202300920

Hyeok Yun, Hyundong Jang, Seunghwan Lee, Junjong Lee, Kyeongrae Cho, Seungjoon Eom, Soomin Kim, Choong-Ki Kim, Hong-Chul Byun, Seongjoo Han, Min-Soo Yoo, Rock-Hyun Baek

{"title":"Nonlinear Variation Decomposition of Neural Networks for Holistic Semiconductor Process Monitoring","authors":"Hyeok Yun, Hyundong Jang, Seunghwan Lee, Junjong Lee, Kyeongrae Cho, Seungjoon Eom, Soomin Kim, Choong-Ki Kim, Hong-Chul Byun, Seongjoo Han, Min-Soo Yoo, Rock-Hyun Baek","doi":"10.1002/aisy.202300920","DOIUrl":"https://doi.org/10.1002/aisy.202300920","url":null,"abstract":"Artificial intelligence (AI) is increasingly used to solve multi-objective problems and reduce the turnaround times of semiconductor processes. However, only brief AI explanations are available for process/device/circuit engineers to provide holistic feedback on the manufactured results. Herein, linear/nonlinear variation decomposition (LVD/NLVD) of neural networks is demonstrated to quantitatively evaluate the influence of unit processes on the figure of merit (FoM) and co-analyze the unit process influences with device characteristic behaviors. The NLVD can evaluate the output variation from each input of neural networks in an individual sample, although neural networks are not available in an analytic form. The NLVD is successfully verified by confirming that a) the output and summation of all decomposed output variations perfectly coincide and b) the process influences on the FoM are decomposed to 6.01–54.86% more accurately compared with those of LVD in 1Y nm node dynamic random-access memory test vehicles with a baseline and split tests introducing high-k metal gates with a minimum gate length of 1 A nm node for further node scaling. The approaches identify defective processes and defect mechanisms in each sample and wafer, which enhance causal analyses for individual cases in diverse fields based on regression artificial neural networks.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"6 10","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202300920","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443572","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

A Cable-Actuated Soft Manipulator for Dexterous Grasping Based on Deep Reinforcement Learning 基于深度强化学习的用于灵巧抓取的线控软机械手

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-08-29 DOI: 10.1002/aisy.202400112

Kunyu Zhou, Baijin Mao, Yuzhu Zhang, Yaozhen Chen, Yuyaocen Xiang, Zhenping Yu, Hongwei Hao, Wei Tang, Yanwen Li, Houde Liu, Xueqian Wang, Xiaohao Wang, Juntian Qu

{"title":"A Cable-Actuated Soft Manipulator for Dexterous Grasping Based on Deep Reinforcement Learning","authors":"Kunyu Zhou, Baijin Mao, Yuzhu Zhang, Yaozhen Chen, Yuyaocen Xiang, Zhenping Yu, Hongwei Hao, Wei Tang, Yanwen Li, Houde Liu, Xueqian Wang, Xiaohao Wang, Juntian Qu","doi":"10.1002/aisy.202400112","DOIUrl":"https://doi.org/10.1002/aisy.202400112","url":null,"abstract":"The growing interest in the flexibility and operational capabilities of soft manipulators in confined spaces emphasizes the need for precise modeling and accurate motion control. Conventional control methods encounter difficulties in modeling and involve intricate computations. This work introduces a novel deep reinforcement learning (DRL) control algorithm based on neural network modeling. Using the Whale Optimization Algorithm, an approximate dynamic model for the soft manipulator is established. The twin delayed deterministic policy gradient is employed for DRL control. Domain randomization is applied during pretraining in a simulated environment. The algorithm addresses issues related to dependency on measurement data quality and redundant mappings, outperforming other methods by 8–15 mm in control accuracy. The trained DRL controller achieves precise trajectory tracking within the soft manipulator's task space, enabling successful grasping tasks in various complex environments, including pipelines and other narrow spaces. Experimental results confirm the autonomy of our controller in performing these tasks without human intervention.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"6 10","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202400112","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142443490","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

Deformable Capsules for Object Detection 用于物体探测的可变形胶囊

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-08-22 DOI: 10.1002/aisy.202400044

Rodney LaLonde, Naji Khosravan, Ulas Bagci

{"title":"Deformable Capsules for Object Detection","authors":"Rodney LaLonde, Naji Khosravan, Ulas Bagci","doi":"10.1002/aisy.202400044","DOIUrl":"https://doi.org/10.1002/aisy.202400044","url":null,"abstract":"Capsule networks promise significant benefits over convolutional neural networks (CNN) by storing stronger internal representations and routing information based on the agreement between intermediate representations’ projections. Despite this, their success has been limited to small-scale classification datasets due to their computationally expensive nature. Though memory-efficient, convolutional capsules impose geometric constraints that fundamentally limit the ability of capsules to model the pose/deformation of objects. Further, they do not address the bigger memory concern of class capsules scaling up to bigger tasks such as detection or large-scale classification. Herein, a new family of capsule networks, deformable capsules (DeformCaps), is introduced to address object detection problem in computer vision. Two new algorithms associated with our DeformCaps, a novel capsule structure (SplitCaps), and a novel dynamic routing algorithm (SE-Routing), which balance computational efficiency with the need for modeling a large number of objects and classes, are proposed. This has never been achieved with capsule networks before. The proposed methods efficiently scale up to create the first-ever capsule network for object detection in the literature. The proposed architecture is a one-stage detection framework and it obtains results on microsoft common objects in context which are on par with state-of-the-art one-stage CNN-based methods, while producing fewer false-positive detection, generalizing to unusual poses/viewpoints of objects.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"6 9","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202400044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142316857","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

Design and Optimization of a Magnetic Field Generator for Magnetic Particle Imaging with Soft Magnetic Materials 设计和优化用于软磁材料磁粉成像的磁场发生器

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-08-22 DOI: 10.1002/aisy.202400017

Fynn Foerger, Marija Boberg, Jonas Faltinath, Tobias Knopp, Martin Möddel

{"title":"Design and Optimization of a Magnetic Field Generator for Magnetic Particle Imaging with Soft Magnetic Materials","authors":"Fynn Foerger, Marija Boberg, Jonas Faltinath, Tobias Knopp, Martin Möddel","doi":"10.1002/aisy.202400017","DOIUrl":"https://doi.org/10.1002/aisy.202400017","url":null,"abstract":"\u0000Magnetic field generators are a key component of Magnetic Particle Imaging (MPI) systems, and their power consumption is a major obstacle on the path to human-sized scanners. Despite their importance, a focused discussion of these generators is rare, and a comprehensive description of the design process is currently lacking. This work presents a methodology for the design and optimization of selection field generators operating with soft magnetic materials outside the linear regime in the context of MPI. Key elements are a mathematical model of magnetic field generators, a formalism for defining field sequences, and a relationship between power consumption and field sequence. These are used to define the design space of a field generator given its system requirements and constraints. The design process is then formulated as an optimization problem. Subsequently, this methodology is then utilized to design a new magnetic field generator specifically for cerebral imaging studies. The optimization result outperforms our existing MPI field generator in terms of power consumption and field of view size, providing a proof-of-concept for the entire methodology. As the approach is very general, it can be extended beyond the MPI context to other areas such as magnetic manipulation of medical devices and micro-robotics.","PeriodicalId":93858,"journal":{"name":"Advanced intelligent systems (Weinheim an der Bergstrasse, Germany)","volume":"6 11","pages":""},"PeriodicalIF":6.8,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aisy.202400017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664999","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

A Bioinspired Robotic Finger for Multimodal Tactile Sensing Powered by Fiber Optic Sensors 由光纤传感器驱动的多模态触觉传感生物启发机器人手指

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-08-18 DOI: 10.1002/aisy.202470034

Baijin Mao, Kunyu Zhou, Yuyaocen Xiang, Yuzhu Zhang, Qiangjing Yuan, Hongwei Hao, Yaozhen Chen, Houde Liu, Xueqian Wang, Xiaohao Wang, Juntian Qu

引用次数: 0

Fluid-Driven Director-Field Design Enables Versatile Deployment of Multistable Structures 流体驱动导向场设计实现了多稳态结构的多功能部署

IF 6.8

Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) Pub Date : 2024-08-18 DOI: 10.1002/aisy.202470039

Yaron Veksler, Ezra Ben-Abu, Amir D. Gat

引用次数: 0