检索结果-内蒙古大学图书馆

Space robotics (iSpaRo), International Conference on

作者： Matteo De Benedetti Steven Kay Jorge Ocón Raquel Jalvo Manuel Esquer Cerezo Augusto Gómez Eguíluz Mercedes Alonso Javier Ramos Fernandez Karl Buckley Robert Field Angus Cameron Vassilios Papantoniou Ares Papantoniou Carlos Perez del Pulgar Konstantinos Kapellos Martin Azkarate GMV NSL Ltd UK GMV Aerospace and Defence Spain Hellenic Technology of Robotics Athens Greece Department of Systems Engineering and Automation Space Robotics Laboratory Universidad de Málaga Málaga Spain Network Research Belgium Uccle Belgium European Space Agency European Space Research and Technology Centre (ESTEC) Noordwijk Netherlands

ISBN: (数字)9798350367232

ISBN: (纸本)9798350367249

Previous Mars and Moon rover missions have highlighted a limitation in mobility, with surface rovers traversing only a few tens of meters per day, at speeds in the order of 10 cm/s. This limitation can be primarily attributed to the rover locomotion system from one side, and on the other by the lack/limited on-board autonomous *** address these limitations, ESA issued a series of activities on fast autonomous rovers. GMV is leading the RAPID and FASTNAV projects, aiming at developing a semi-autonomous rover capable of safely traversing lunar terrains at high speeds (around 1 m/s), using a visual navigation based Guidance, Navigation and Control (GNC) system. The RAPID project was the foundation of this work, in which the rover platform was designed, manufactured, and a first version of the on-board software was developed. The follow-up FASTNAV project builds upon the work of RAPID to establish an innovative multi-mode continuous drive GNC system. This new architecture aims to achieve an improved autonomy and faster speeds, with different guidance modes selected according to the terrain type, using a combination of techniques (AI and classical computer vision), while also improving the existing GNC *** paper shall present the experience obtained during the development of the rover platform and the GNC system across both activities. It shall provide an overview of the challenges and risks, the decisions made, a detailed technical overview of the GNC architecture and components, and the results observed during the analogue field tests.

关键词： Space vehicles Meters Visualization Computer vision Navigation Space missions Moon Computer architecture Control systems Software

来源：评论

学校读者我要写书评

暂无评论

A Context-Enhanced Full-Resolution Floor Plan Segmentation Network for Topological Semantic Mapping

A Context-Enhanced Full-Resolution Floor Plan Segmentation N...

引用

IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zhengcai Cao Yiyang Sun Zhe Ma MengChu Zhou State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Information Science and Technology Beijing University of Chemical Technology Beijing China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Topological semantic maps provide a practical solution to enhance indoor navigation for the Partially Sighted or Visually Impaired (PSVI). Segmenting indoor floor plans and extracting boundaries are key to constructing these maps. The existing methods exhibit low accuracy in segmentation. To achieve desired high segmentation accuracy, we introduce a Context-Enhanced Full-Resolution Network (CEFRN) for floor plan segmentation. It is designed to harness the shallow detailed features and inter-category contextual dependencies inherent in floor plans. CEFRN integrates modified residual blocks to capture the low-stage full-resolution features while maintaining its compactness. A position attention module is employed to refine the deep-stage contextual information. We also propose a two-dimensional deep supervision method to merge features from both stages, which significantly boosts the feature representation ability of CEFRN. Finally, a practical topological semantic mapping method for PSVI indoor navigation is introduced. Experimental results demonstrate that CEFRN’s segmentation accuracy well exceeds the state-of-the-art methods’. It can be used to well support accurate topological semantic mapping.

关键词： Accuracy Hospitals Indoor navigation Semantics Feature extraction Mobile robots Floors Intelligent robots Autonomous vehicles Drones

来源：评论

学校读者我要写书评

暂无评论

Edge Detectors Can Make Deep Convolutional Neural Networks More Robust

arXiv

引用

arXiv 2024年

作者： Ding, Jin Zhao, Jie-Chao Sun, Yong-Zhi Tan, Ping Wang, Jia-Wei Ma, Ji-En Fang, You-Tong School of Automation and Electrical Engineering Key Institute of Robotics of Zhejiang Province Zhejiang University of Science and Technology Hangzhou310023 China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China School of Electrical Engineering Zhejiang University Hangzhou310027 China

Deep convolutional neural networks (DCNN for short) are vulnerable to examples with small perturbations. Improving DCNN’s robustness is of great significance to the safety-critical applications, such as autonomous driving and industry automation. Inspired by the principal way that human eyes recognize objects, i.e., largely relying on the shape features, this paper first employs the edge detectors as layer kernels and designs a binary edge feature branch (BEFB for short) to learn the binary edge features, which can be easily integrated into any popular backbone. The four edge detectors can learn the horizontal, vertical, positive diagonal, and negative diagonal edge features, respectively, and the branch is stacked by multiple Sobel layers (using edge detectors as kernels) and one threshold layer. The binary edge features learned by the branch, concatenated with the texture features learned by the backbone, are fed into the fully connected layers for classification. We integrate the proposed branch into VGG16 and ResNet34, respectively, and conduct experiments on multiple datasets. Experimental results demonstrate the BEFB is lightweight and has no side effects on training. And the accuracy of the BEFB integrated models is better than the original ones on all datasets when facing FGSM, PGD, and C&W attacks. Besides, BEFB integrated models equipped with the robustness enhancing techniques can achieve better classification accuracy compared to the original models. The work in this paper for the first time shows it is feasible to enhance the robustness of DCNNs through combining both shape-like features and texture features. © 2024, CC BY-NC-SA.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

High-compatibility Manipulation Method for Parallel In-situ Isolation of Microalgal Cells via Optoelectronic Tweezers

High-compatibility Manipulation Method for Parallel In-situ ...

引用

IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Shilong Qin Jiaxin Liu Yuxin Chen Haotian Yang Ziyi Zhao Qing Shi Qiang Huang Huaping Wang Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing China School of Mechatronical Engineering Beijing Institute of Technology Intelligent Robotics Institute Beijing China School of Medical Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

Isolating microalgae in in-situ liquid environment based on optoelectronic tweezers (OETs) enables providing specific species of microalgae in high-purity, thus has significant potential in environmental detection, aquaculture, bioenergy, and biomedicine development. However, the conventional OET method can only separate and extract one type of microalgae in a single-step operation and is challenging to utilize the opposite dielectrophoretic force when the cross frequency of microalgae is too high /low or even absent. In this study, a novel automated microalgae isolation method based on optoelectronic tweezers is proposed, which integrates two strategies: cluster manipulation and discretized synchronous manipulation. Firstly, an optoelectronic tweezer robot platform was built, the dielectrophoretic forces on microalgae and the factors affecting the dielectrophoretic forces were analyzed. Secondly, a cluster manipulation strategy based on light patterns dynamic locomotion structure scheme was designed to simultaneously separate microalgae subject to dielectrophoretic forces of different attributes and the same attribute. Finally, a discretized synchronous manipulation strategy based on visual feedback and PID controller was designed to realize the precise isolation of microalgae subjected to the same dielectrophoretic force and different dielectrophoretic forces. Experimental results demonstrated that the aforementioned method provides a feasible microalgae isolating method based on optoelectronic tweezers within 10 minutes, which has potential applications in the in-situ water contamination detection and treatment.

关键词： Visualization Liquids Force Dynamics Water pollution Real-time systems Dielectrophoresis

来源：评论

学校读者我要写书评

暂无评论

SAD-TIME: a Spatiotemporal-fused network for depression detection with Automated multi-scale Depth-wise and TIME-interval-related common feature extractor

arXiv

引用

arXiv 2024年

作者： Wang, Han-Guang Hou, Hui-Rang Jin, Li-Cheng Xu, Chen-Yang Zhang, Zhong-Yi Meng, Qing-Hao Zhang, Yong-Hui Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin300072 China Department of Psychiatry Tianjin Anding Hospital Mental Health Center Tianjin Medical University China

Background and Objective: Depression is a severe mental disorder, and accurate diagnosis is pivotal to the cure and rehabilitation of people with depression. However, the current questionnaire-based diagnostic methods could bring subjective biases and may be denied by subjects. In search of a more objective means of diagnosis, researchers have begun to experiment with deep learning-based methods for identifying depressive disorders in recent years. Methods: In this study, a novel Spatiotemporal-fused network with Automated multi-scale Depth-wise and TIME-interval-related common feature extractor (SAD-TIME) is proposed. SAD-TIME incorporates an automated nodes’ common features extractor (CFE), a spatial sector (SpS), a modified temporal sector (TeS), and a domain adversarial learner (DAL). The CFE includes a multiscale depth-wise 1D-convolutional neural network and a time-interval embedding generator, where the unique information of each channel is preserved. The SpS fuses the functional connectivity with the distance-based connectivity containing spatial position of EEG electrodes. A multi-head-attention graph convolutional network is also applied in the SpS to fuse the features from different EEG channels. The TeS is based on long short-term memory and graph transformer networks, where the temporal information of different time-windows is fused. Moreover, the DAL is used after the SpS to obtain the domain-invariant feature. Results: Experimental results under tenfold cross-validation show that the proposed SAD-TIME method achieves 92.00% and 94.00% depression classification accuracies on two datasets, respectively, in cross-subject mode. Conclusion: SAD-TIME is a robust depression detection model, where the automatedly-generated features, the SpS and the TeS assist the classification performance with the fusion of the innate spatiotemporal information in the EEG signals. Copyright © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

In Situ Measurement of the Kinetic Friction of Si Nanowires on SiC Substrates in SEM with a Microprobe 11

In Situ Measurement of the Kinetic Friction of Si Nanowires ...

引用

11th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2021

作者： Gao, Peng Zhou, Jie Zou, Tao Rong, Weibin State Key Laboratory of Robotics and Systems Harbin Institute of Technology HarbinHeilongjiang150080 China School of Electrical and Control Engineering Heilongjiang University of Science and Technology HarbinHeilongjiang150022 China

ISBN: (纸本)9781665425278

This research introduces a kinetic friction modeling and measurement method for silicon nanowires (NWs) and silicon carbide substrates. The NW was pushed to slide by the micro-force probe at a constant speed. Under the conditions of kinetic friction and deformation of the nanowires, the silicon nanowires are in equilibrium during the measurement. Under this condition, the value measured by the micro-force probe is the total kinetic friction force. The thermal insulation connector is used to isolate the heat conduction to the micro-force probe to avoid the influence of temperature rise on the measurement result. The Faraday cup was used to measure the surface current in the scanning electron microscope (SEM). The appropriate parameters of SEM were chosen according to the surface current to reduce the influence of the charging effect on the measurement results. The high sensitivity of the micro-force probe is used to ensure that there is no contact between the probe and the substrate, thereby avoiding the interference of the pre-load force. The entire experiment process was monitored in real-time to improve the stability of the measurement. The study in this paper found that the shear stress of silicon nanowires is 1.05 \pm 0.32\text{MPa}. © 2021 IEEE.

关键词： Silicon carbide

来源：评论

学校读者我要写书评

暂无评论

BLIP-Adapter: Bridging Vision-Language Models with Adapters for Generalizable Face Anti-spoofing 18

BLIP-Adapter: Bridging Vision-Language Models with Adapters ...

引用

18th IEEE International Joint Conference on Biometrics, IJCB 2024

作者： Zhang, Bin Zhu, Xiangyu Gao, Li Zhang, Xiaoyu Lei, Zhen Chinese Academy of Sciences Institute of Information Engineering China University of Chinese Academy of Sciences School of Cyber Security China China Mobile Financial Technology Co. Ltd. China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation China University of Chinese Academy of Sciences School of Artificial Intelligence China Chinese Academy of Sciences Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation Hong Kong

ISBN: (纸本)9798350364132

Face anti-spoofing is essential for ensuring the security of facial recognition systems against spoofing attacks. Recent methods have transferred Vision-Language models to face anti-spoofing (e.g., FLIP and CLIPC8), demonstrating that learning perception from supervision in natural language can enhance the model's detection performance. However, such methods exhibit limited depth in the interaction between images and texts, resulting in poor performance on fine-grained understanding tasks such as face anti-spoofing. Besides, the lack of diversity in image-text pairs for face anti-spoofing further hinders such methods from playing their best. To address these issues, we propose a novel fine-tuning strategy for Vision-Language models in face anti-spoofing. This strategy introduces the Bootstrapping Language-Image Pre-training model (BLIP), known for its novel interaction mechanisms and superior image-text comprehension, to construct a more generalized feature representation for face anti-spoofing. Furthermore, we propose an Adapter module for the text branch to reduce the negative impact of insufficient data diversity and catastrophic forgetting. Extensive experiments conducted on various cross-domain testing benchmarks demonstrate the significant superiority of our method over the state-of-the-art, highlighting its effectiveness and robustness. © 2024 IEEE.

关键词： Visual languages

来源：评论

学校读者我要写书评

暂无评论

Key Parameters Prediction for Intelligent Control and Energy Optimization Based on MIC-BWO-XGBoost 2

Key Parameters Prediction for Intelligent Control and Energy...

引用

2nd International Conference on Cyber-Energy systems and Intelligent Energy, ICCSIE 2024

作者： Lv, Changyao Wang, Yaqi Chen, Yudong Yu, Zhuo Hu, Guoliang Wu, Hongliang Li, Shuai Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China College of Information Engineering Shenyang University of Chemical Technology Shenyang110142 China Shanghai Aircraft Manufacturing Co. Ltd. Shanghai201324 China

ISBN: (纸本)9798350373318

In the aviation industry, anodic oxidation serves as a core process for surface modification of aluminum alloy components, albeit accompanied by high energy consumption. Accurate prediction of key parameters can offer decision support for the intelligent control and energy optimization of anodic oxidation. However, the limited sample size resulting from the high cost of data collection and the complex nonlinear patterns caused by the synergy of multiple factors pose a challenge in accurately predicting key parameters. Therefore, we propose a key parameters prediction method based on the Maximum Information Coefficient (MIC), Beluga Whale Optimization algorithm (BWO), and XGBoost algorithm. Considering the adverse impact of low correlation parameters on prediction accuracy, we first use MIC to extract features from the original data. Then, XGBoost is used to integrate multiple decision trees to ensure the strong fitting ability for nonlinear relationships. Compared to deep learning models, XGBoost performs well even in a limited sample size. In addition, considering XGBoost is prone to overfitting training data as an ensemble learning algorithm, we employ the BWO to optimize four key parameters of the model that are difficult to choose, thereby enhancing model's generalization. The model's performance is evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with values of 0.04388, 0.09410, and 0.20730%, respectively. The experimental results demonstrate that the proposed method outperforms traditional approaches, enabling precise prediction of key parameters and holding significant value for the intelligent control and energy optimization of anode oxidation processes. © 2024 IEEE.

关键词： Anodic oxidation

来源：评论

学校读者我要写书评

暂无评论

Mode-switching single-pixel imaging via a high-performance perovskite-Si dual-mode photodetector

引用

Photonics Research 2024年第12期12卷 2873-2880页

作者： YUJIN LIU DONGXU LIN JINGYANG XING HANYAN ZHAO HONGLING WAN HAO WANG ZHONG JI XUELI CHEN Innovation Center for Advanced Medical Imaging and Intelligent Medicine Guangzhou Institute of TechnologyXidian UniversityGuangzhou 510555China Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Department of Mechanical and Energy EngineeringSUSTech Energy Institute for Carbon NeutralitySouthern University of Science and TechnologyShenzhen 518055China Center for Biomedical-Photonics and Molecular Imaging Advanced Diagnostic-Therapy Technology and Equipment Key Laboratory of Higher Education Institutions in Shaanxi ProvinceSchool of Life Science and TechnologyXidian UniversityXi’an 710126China

Visible–near-infrared(VIS-NIR)dual-mode imaging can expand the human perception ***,the development of dual-mode image sensors is still challenging due to complex fabrication processes and readout circuit ***,we design a simple-structured(perovskite-Au/Si/Ag)dual-mode *** unique asymmetric electrode design allows the device to support two operating modes at zero *** device exhibits a detection range covering 400–1100 nm under top illumination mode,with a peak specific detectivity of up to 5.56×1013 *** bottom illumination mode,the device demonstrates pronounced narrowband NIR response *** importantly,we develop a dual-mode single-pixel imaging system based on this device,bypassing the fabrication processes of high-density array image *** system exhibits excellent VISNIR dual-mode imaging results,effectively separating NIR and VIS information and enhancing infrared details in the fused ***,we discover that the system can effectively suppress ringing artifacts,achieving infrared information perception at a low sampling rate,which can accelerate the imaging speed by∼16 times(reduced from∼3.2 s to∼0.2 s).Our proposed dual-mode single-pixel imaging technology offers new means for material identification and intelligent perception.

关键词： mode illumination details

来源：评论

学校读者我要写书评

暂无评论

Uapgo: Uncertainty-Aware Pose Graph Optimization for Lidar-Based Slam systems

SSRN

引用

SSRN 2024年

作者： Zhi, Tian Xu, Jie Ma, Yongxin Yu, Wenlu Liu, Shenglan Yuan, Shenghai College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics Jiangsu Nanjing210016 China School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150001 China School of Mechanical Engineering Shandong University Jinan250061 China

Addressing uncertainty errors, although crucial, may sometimes be deprioritized in the optimization process ofLiDAR-based SLAM systems due to the inherent complexity of the task. The practice of applying uniform weights, which simplifies the uncertainty management, when incorporating factors can inadvertently degrade the pose graph optimization, particularly within complex environments. In response to this, we propose anuncertainty-aware pose graph optimization technique, along with an innovative keyframe selection strategy. We develop a model for estimating the covariance of relative pose transformations, utilizing frontend odometry output and the Huber robust kernel function. This model assigns weights based on the uncertainty error of pose transformations. Upon detection of a loop closure, the system optimizes keyframe poses, effectively reducing cumulative error. Our keyframe selection strategy takes into account the maximum eigenvalue of the translational component of pose covariance as an uncertainty measure. If this value surpasses a certain threshold, the pose is selected as a keyframe, thereby enhancing data precision and computational efficiency, and subsequently improving the SLAM system’s ability to handle uncertainty. Ablation studies validate our approach, demonstrating its effectiveness in enhancing performance, especially in complex environments and conditions of data degradation. Wealso provide the associated open-source code for further research. © 2024, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：