检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

24,329 篇 会议
164 篇 期刊文献
56 册 图书
1 篇 学位论文
1 篇 科技报告

馆藏范围

24,551 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

10,064 篇 工学
- 6,293 篇 控制科学与工程
- 4,058 篇 计算机科学与技术...
- 2,626 篇 软件工程
- 2,114 篇 电气工程
- 1,861 篇 机械工程
- 1,145 篇 仪器科学与技术
- 707 篇 信息与通信工程
- 586 篇 生物工程
- 469 篇 生物医学工程（可授...
- 419 篇 光学工程
- 399 篇 力学（可授工学、理...
- 360 篇 电子科学与技术（可...
- 262 篇 化学工程与技术
- 248 篇 交通运输工程
- 247 篇 材料科学与工程（可...
- 240 篇 动力工程及工程热...
- 214 篇 土木工程
- 201 篇 建筑学
- 180 篇 安全科学与工程
3,052 篇 理学
- 1,751 篇 数学
- 897 篇 物理学
- 640 篇 生物学
- 580 篇 统计学（可授理学、...
- 484 篇 系统科学
- 229 篇 化学
1,222 篇 管理学
- 957 篇 管理科学与工程(可...
- 312 篇 工商管理
- 306 篇 图书情报与档案管...
322 篇 医学
- 284 篇 临床医学
- 204 篇 基础医学(可授医学...
124 篇 经济学
105 篇 法学
86 篇 农学
52 篇 教育学
27 篇 文学
16 篇 军事学
13 篇 艺术学
1 篇 哲学

主题

2,436 篇 predictive model...
1,965 篇 robots
1,825 篇 robotics and aut...
1,708 篇 computational mo...
1,699 篇 automation
1,618 篇 data models
1,570 篇 robot sensing sy...
1,470 篇 analytical model...
1,372 篇 adaptation model...
1,359 篇 training
1,141 篇 mathematical mod...
1,099 篇 accuracy
1,090 篇 trajectory
1,042 篇 mobile robots
884 篇 feature extracti...
836 篇 robot kinematics
825 篇 robustness
790 篇 control systems
711 篇 solid modeling
694 篇 cameras

机构

181 篇 university of ch...
143 篇 school of artifi...
111 篇 robotics institu...
87 篇 school of automa...
82 篇 institute of aut...
71 篇 shenyang institu...
70 篇 institutes for r...
68 篇 the robotics ins...
68 篇 school of electr...
63 篇 state key labora...
61 篇 school of mechat...
50 篇 department of au...
49 篇 department of au...
48 篇 state key labora...
46 篇 school of automa...
44 篇 school of mechan...
41 篇 robotics institu...
39 篇 school of automa...
31 篇 school of automa...
29 篇 carnegie mellon ...

作者

37 篇 secchi cristian
34 篇 yuechao wang
32 篇 yun-hui liu
31 篇 cristian secchi
29 篇 shugen ma
28 篇 lining sun
24 篇 xiang li
22 篇 jian wang
22 篇 jianda han
22 篇 fabio ramos
20 篇 xinyu wu
20 篇 wu xinyu
20 篇 daniela rus
19 篇 tomizuka masayos...
19 篇 wei li
19 篇 levine sergey
18 篇 c. laugier
18 篇 chen chen
18 篇 dinesh manocha
18 篇 cesare fantuzzi

语言

24,231 篇 英文
236 篇 其他
91 篇 中文
2 篇 西班牙文
1 篇 俄文

检索条件"任意字段=International Conference on Methods and Models in Automation and Robotics"

共 24551 条记录，以下是31-40 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

A LLM-Based Robot Partner with Multi-modal Emotion Recognition 17th

A LLM-Based Robot Partner with Multi-modal Emotion Recogniti...

引用

17th international conference on Intelligent robotics and Applications

作者： Jiang, Yutong Shao, Shuai Dai, Yaping Hirota, Kaoru Beijing Inst Technol Beijing 100081 Peoples R China

ISBN: (纸本)9789819607853;9789819607860

The integration of Large Language models (LLMs) with robotic systems has opened new avenues for the development of empathetic and interactive robot partners. This paper introduces a service robot system that incorporates multi-modal emotion recognition and LLM-based emotion dialogue generation. The system captures user emotions through a tri-modal emotion recognition model (TriMER), which processes audio, text, and facial expressions using advanced techniques like BiLSTM, CNN, and Deformable Convolutional Networks (DCN). Experiments conducted using the IEMOCAP dataset show that our TriMER model achieves an accuracy of 74.15% in recognizing emotions. By combining emotion recognition with LLM, the robot can better understand and respond to human emotions, facilitating more natural and empathetic interactions. This development holds promise for applications in elder care, aiming to enhance both physical and mental well-being.

关键词： Robot Partners Multi-modal Emotion Recognition Large Language models Human-Robot Interaction

来源：评论

学校读者我要写书评

暂无评论

Free-Form Instruction Guided Robotic Navigation Path Planning with Large Vision-Language Model 17th

Free-Form Instruction Guided Robotic Navigation Path Plannin...

引用

17th international conference on Intelligent robotics and Applications

作者： Du, Yuhao Wu, Chengzhong Feng, Mingtao Luo, Jianqiao Zhong, Hang Miao, Zhiqiang Wang, Yaonan Xidian Univ Xian Peoples R China Jiangxi Prov Commun Terminal Ind Co Ltd Xian Peoples R China Hunan Univ Changsha Peoples R China

ISBN: (纸本)9789819607884;9789819607891

The integration of multiple pre-trained models in robotic navigation has the advantage of combining diverse strengths, leading to robust and generalized performance. However, the effectiveness of these models is often limited by path planning strategies, necessitating improvements in navigation capabilities. To overcome this, we introduce the Free-form Instruction Guided Robotic Navigation Path Planning with Large Vision-Language Model (FIG-RN). This model leverages free-form instructions to extract landmarks and directional cues, utilizing a pre-trained visual-language model to associate these landmarks with map nodes, thereby laying the groundwork for subsequent path planning. It evaluates landmark-node matches, node accessibility, and orientation to optimize path planning. Compared to traditional models, FIG-RN offers significant benefits: (i) it requires no map annotations due to its use of high-quality pre-trained models, (ii) it maximizes information use from instructions for better path efficacy, and (iii) it refines visual-language model matching values for improved local navigation. Experimentally, FIG-RN outperforms LM-Nav in success rate, efficiency, and accuracy, with improvements of 0.2, 0.2143, and 0.208, respectively.

关键词： Robotic Navigation Path Planning Pre-trained models Free-form Instructions

来源：评论

学校读者我要写书评

暂无评论

Enhancing Troubleshooting Task-Oriented Dialog Systems with Large Language models 1

引用

17th international conference on Intelligent robotics and Applications

作者： Zhou, Jiahao Zhang, Qiang Zhang, Fengda Yuan, Caixia Beijing Univ Posts & Telecommun Beijing Peoples R China State Grid Smart Grid Res Inst CoLtd Beijing Peoples R China State Grid Shandong Elect Power Res Inst Jinan Peoples R China

ISBN: (数字)9789819607921

ISBN: (纸本)9789819607914;9789819607921

Task-oriented dialog (TOD) systems use external knowledge sources to help users accomplish specific tasks. While most current TOD research focuses on simple information-collecting tasks in a slot-filling framework, multi-step reasoning tasks like troubleshooting remain under-explored. Leveraging the advancements of large language models (LLMs), we propose a novel LLM-based multi-agent learning framework to build troubleshooting dialogue systems and evaluate the effectiveness of various multi-agent learning settings in a TOD system. Our results show that LLMs designed for open-domain dialog face challenges when directly applied to TOD systems, but with multi-agent cooperative enhancements, LLMs can achieve commendable performance.

关键词： Large Language Model Task Oriented Dialog System Multi-agent

来源：评论

学校读者我要写书评

暂无评论

Enhancing GPS/IMU Localization Accuracy in Autonomous Vehicles through Deep Learning-Based Error Correction models

Enhancing GPS/IMU Localization Accuracy in Autonomous Vehicl...

引用

9th international conference on Mechanical Engineering and robotics Research, ICMERR 2025

作者： Onyema, Uchenna Charles Mahmoud, Shafik College of Science and Engineering University of Derby Derby United Kingdom

ISBN: (纸本)9798331509262

Improving the precision of GPS/IMU localisation in autonomous cars is crucial for ensuring safe and efficient navigation. Several research studies have concentrated on enhancing the precision of localisation systems by employing sensor fusion and sophisticated algorithms. This study proposes a novel approach to enhance GPS/IMU localization accuracy in autonomous vehicles using deep learning-based error correction models. Leveraging Long Short-Term Memory (LSTM) networks, the method captures and corrects inherent errors in GPS/IMU data, leading to significantly improved positional accuracy. The LSTM model was meticulously designed to process sequential data, incorporating an LSTM layer with 50 units to capture temporal relationships and a Dense output layer to predict corrected longitude and latitude values. The model was trained using the Adam optimizer and mean squared error (MSE) loss function, achieving notable reductions in prediction error across 50 epochs. Comparative analyses between actual and predicted coordinates demonstrated the model's high precision. The model was further validated through deployment in a Flask application for continuous testing and a web application for real-time tracking of autonomous vehicles. Results underscore the potential of deep learning models to substantially improve localization accuracy, thereby enhancing the reliability and performance of autonomous navigation systems. © 2025 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Novel Flapping-Wing Micro Aerial Vehicles Utilising Dynamic Amplification

Novel Flapping-Wing Micro Aerial Vehicles Utilising Dynamic ...

引用

9th international conference on Mechanical Engineering and robotics Research, ICMERR 2025

作者： Park, Moonsoo Abolfathi, Ali Mechanical Engineering University College London London United Kingdom

ISBN: (纸本)9798331509262

This paper introduces a novel design for flapping wing micro aerial vehicles (FWMAVs) that employs dynamic amplification. By utilising mechanical resonance, the design amplifies wing stroke and pitching motions, reducing the energy requirement while enhancing lift production. This approach also minimises the maximum strain on the actuator, thereby improving its structural integrity. A comprehensive mathematical model of the flapping mechanism is developed, incorporating the electromechanical characteristics of piezoelectric materials, nonlinear structural dynamics and aerodynamics. Numerical simulations using MATLAB and Simulink demonstrate the advantages of dynamic amplification, showing a significant improvement in lift generation compared to rigidly structured flapping systems. Using a practical actuator and wing setup, the model predicts a stroke angle of 45 °, a pitching angle of 67 °, a lift generation of 28.4 mN, and average input and output powers of 6.7 mW and 2.9 mW, respectively. This design approach offers a promising pathway for developing high-performance FWMAVs, with potential applications in autonomous flight operations. © 2025 IEEE.

关键词： Numerical models

来源：评论

学校读者我要写书评

暂无评论

Comparison of Different Weld Bead Area Prediction models for Overlay Deposition by Robot-Based Cold Metal Transfer Process

Comparison of Different Weld Bead Area Prediction Models for...

引用

9th international conference on Mechanical Engineering and robotics Research, ICMERR 2025

作者： Patel, Nitin Jha, Sunil Nohwal, Aman Indian Institute of Technology Delhi Department of Mechanical Engineering New Delhi India

ISBN: (纸本)9798331509262

Arc welding, a predominant joining process, is increasingly being utilized in new applications, particularly metal 3D printing. Before 3D printing a part, its 3D CAD model is sliced into thin layers. Accurate identification of the geometry of individual layers and proper hatch spacing between these layers are equally important. Both factors significantly influence the quality of the final metal part printed by a robot-based Cold metal transfer wire arc additive manufacturing (CMT-WAAM) process. Experiments were conducted based on a two-factor central composite rotatable design. The bead area measured from the bead profile is compared with the area predicted by different bead models and, it was found that at lower wire feed speed to torch ratio (A 8), the circular model best predicts the weld profile area. Further, these models have been utilized to identify the optimum hatch spacing, so that proper area filling could be achieved during the CMT-W AAM process. Based on this prediction, multi-bead horizontal overlay experiments were conducted that were found free from any kind of lack of fusion voids and produced minimal surface waviness. Extended inter-layer dwell time reduces heat accumulation but increases surface waviness and lack of fusion voids due to arc deflection and misalignment, resulting in uneven bead heights. © 2025 IEEE.

关键词： Inert gas welding

来源：评论

学校读者我要写书评

暂无评论

End-to-End Deep Learning models for Estimating Stride Length in Frail Older Adults 24

End-to-End Deep Learning Models for Estimating Stride Length...

引用

2nd international conference on Frontiers of Intelligent Manufacturing and automation, CFIMA 2024

作者： Zhang, Yan Cai, Jinghao Li, Xiang Wu, Chuanyan Ma, Xin Li, Yibin Song, Rui Zhang, Huanghe School of Control Science and Engineering Shandong University Shandong China The Center for Robotics School of Control Science and Engineering Shandong University Shandong China School of Intelligent Engineering Shandong Management University Shandong China

ISBN: (纸本)9798400710681

Accurate estimation of spatial gait parameters is crucial for assessing fall risk in older adults, helping to identify potential movement impairments and prevent falls. Traditionally, extracting stride length from wearable sensors relies on the double integration of accelerometer data combined with the zero-velocity update (ZUPT) technique. However, this method may not be suitable for older adults, as their zero-velocity phases might be absent. To address this limitation, we propose three fundamental end-to-end deep learning models—deep neural networks (DNN), deep convolutional neural networks (DCNN), and long short-term memory (LSTM)—to estimate stride length from inertial sensor data corresponding to specific strides. These models are trained on a publicly available dataset (i.e., GSTRIDE) comprising 165,694 strides from 155 elderly patients and are evaluated using hold-out and 10-fold cross-validation methodologies. The DCNN model achieved the best results, with a mean absolute error (MAE) of 8.9 cm using the hold-out method. Compared to the traditional double integration method, the proposed deep learning models do not require zero-velocity phase detection. Instead, they rely on initial contact detection, making them more suitable for older adults, where initial contacts can be reliably detected even when they do not occur under the hindfoot. © 2024 Copyright held by the owner/author(s).

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Diffusion models are Good Unsupervised Class-agnostic Shape Part Segmentators

Diffusion Models are Good Unsupervised Class-agnostic Shape ...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Jiang, Zhongbin Shi, Tianhao Gao, Hao Liu, Jun Liu, Ye School of Automation and Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing China School of Computing and Communications Lancaster University United Kingdom

ISBN: (纸本)9798350368741

Shape part segmentation is a critical task in computer graphics and robotics. However, traditional supervised methods rely heavily on large amounts of labeled data, which poses significant challenges in many real-world scenarios where such data is often scarce or difficult to obtain. To address this issue, we propose an unsupervised, class-agnostic part segmentation method called Point Diffusion Segmentation (PDS). Our research demonstrates that unconditional point cloud diffusion models can capture abstract object concepts within their sub-attention layers. By extracting preliminary point cloud features from these attention maps, PDS generates efficacious segmentation results. This method fully leverages unlabeled data and proves to be highly applicable in various downstream tasks, including zero-shot part segmentation. Without resorting to any labeled data, PDS improves the zero-shot part segmentation performance of PointClipV2 by 3.1% on the ShapeNet Part dataset, setting a new state-of-the-art baseline and demonstrating significant potential of PDS. © 2025 IEEE.

关键词： class-agnostic segmentation diffusion model unsupervised zero-shot

来源：评论

学校读者我要写书评

暂无评论

Design for Robot-Based Non-Planar Additive Manufacturing Case Study: Soft robotics Gripper

Design for Robot-Based Non-Planar Additive Manufacturing Cas...

引用

9th international conference on Mechanical Engineering and robotics Research, ICMERR 2025

作者： Gil-Villacastin, Laura Guzman-Bautista, Alvaro Lopez-Arrabal, Adrian Chacon-Tanarro, Enrique Sancho-Arellano, Amparo Lerin-Alonso, Miguel Universidad Politecnica de Madrid ETSI Industriales Mech. Eng. Dept. Madrid Spain

ISBN: (纸本)9798331509262

Robot-based Non-Planar Additive Manufacturing, as a manufacturing technique, may be a candidate for the fabrication of soft robotics compliant mechanisms, owing to the increased design freedom and final part mechanical properties of these methods compared to conventional Additive Manufacturing. The non-planar slicing method applied in this work involves the bijective homomorphism between the Cartesian map and a slicing map, used for planar part design. This paper explores this novel Design for Non-Planar Additive Manufacturing technique and applies it on a case study of a Yoshimura-style origami compliant mechanism-based grasping end-effector. Three different build platforms are proposed for different to-be-grasped applications. For all three cases, the complete methodology is applied, starting from CAD model preparation, model isomorphism onto the Cartesian map, planar additive manufacturing trajectory generation and toolpath isomorphism for manufacturing. This case study showcases the possibilities of Robot-based Non-Planar Additive Manufacturing for the manufacture of improved mechanical properties soft robotics compliant mechanisms, and suggests the transversality of the methodology for other areas of knowledge, including aerospace, embedded electronics, and biomedical industries. © 2025 IEEE.

关键词： Grippers

来源：评论

学校读者我要写书评

暂无评论

Underwater Image Denoising and Enhancement via Diffusion models and Attention Mechanisms 24

Underwater Image Denoising and Enhancement via Diffusion Mod...

引用

4th international conference on Signal Processing and Communication Technology, SPCT 2024

作者： Chen, Wei Gong, Chengxin Liu, Yanghe Wu, Bodong Zhu, Minrui Moscow State University Moscow Russia Shenzhen MSU-BIT University Guangdong Shenzhen China

ISBN: (纸本)9798400710636

Underwater images are widely used in marine science, ocean engineering, and underwater robotics. However, challenges such as insufficient lighting, scattering, and absorption often degrade image quality, limiting their effectiveness. To address this, we propose AquaDiffusionNet, a model combining Diffusion models and Attention Mechanisms for underwater image denoising and enhancement. Built on the U-Net architecture, it removes complex noise using diffusion models and captures critical features through multi-head attention mechanisms. AquaDiffusionNet achieves simultaneous denoising and detail enhancement, improving image contrast and clarity. Experiments on public datasets like UIEB show significant performance gains, with PSNR increased by 3.0 dB and SSIM by 0.07, outperforming traditional methods. This model enhances visual quality and provides superior input for subsequent image analysis, driving advancements in underwater vision technology. © 2024 Copyright held by the owner/author(s).

关键词： Underwater imaging

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共500页 << < 1 2 3 4 5 6 7 8 9 10 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：