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

2,879 篇 会议
135 册 图书
88 篇 期刊文献
1 篇 科技报告

馆藏范围

3,103 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

1,342 篇 工学
- 862 篇 控制科学与工程
- 765 篇 计算机科学与技术...
- 518 篇 软件工程
- 188 篇 电气工程
- 171 篇 机械工程
- 121 篇 信息与通信工程
- 96 篇 电子科学与技术（可...
- 88 篇 仪器科学与技术
- 70 篇 光学工程
- 67 篇 生物工程
- 66 篇 建筑学
- 66 篇 土木工程
- 65 篇 生物医学工程（可授...
- 53 篇 力学（可授工学、理...
- 50 篇 航空宇航科学与技...
- 46 篇 交通运输工程
- 40 篇 化学工程与技术
- 36 篇 安全科学与工程
- 34 篇 动力工程及工程热...
457 篇 理学
- 277 篇 数学
- 127 篇 物理学
- 77 篇 统计学（可授理学、...
- 76 篇 生物学
- 54 篇 系统科学
- 44 篇 化学
245 篇 管理学
- 212 篇 管理科学与工程(可...
- 73 篇 工商管理
- 45 篇 图书情报与档案管...
40 篇 医学
- 35 篇 临床医学
- 32 篇 基础医学(可授医学...
25 篇 经济学
23 篇 法学
8 篇 教育学
8 篇 农学
8 篇 军事学
1 篇 艺术学

主题

496 篇 computational mo...
302 篇 artificial intel...
299 篇 robotics and aut...
250 篇 computational in...
225 篇 robot sensing sy...
210 篇 mobile robots
196 篇 intelligent robo...
181 篇 automation
178 篇 control systems
161 篇 humans
158 篇 robots
134 篇 orbital robotics
121 篇 robot kinematics
117 篇 navigation
115 篇 robotics
109 篇 service robots
103 篇 neural networks
103 篇 mathematical mod...
97 篇 automatic contro...
90 篇 robustness

机构

26 篇 school of automa...
25 篇 department of au...
23 篇 school of automa...
21 篇 computer and aut...
19 篇 college of intel...
19 篇 department of au...
17 篇 dept. of automat...
15 篇 institute of aut...
14 篇 hubei key labora...
14 篇 unmanned system ...
14 篇 nanjing universi...
14 篇 doctoral school ...
11 篇 state key labora...
10 篇 óbuda university...
10 篇 school of mechat...
10 篇 department of au...
10 篇 school of artifi...
9 篇 antal bejczy cen...
9 篇 dep. of electric...
9 篇 university of ch...

作者

29 篇 radu-emil precup
20 篇 stefan preitl
18 篇 ioan filip
17 篇 józsef k. tar
15 篇 hirota kaoru
14 篇 tamás haidegger
14 篇 yifeng niu
14 篇 dai yaping
14 篇 wenxing fu
14 篇 yi qu
13 篇 octavian prostea...
12 篇 iosif szeidert
12 篇 precup radu-emil
11 篇 preitl stefan
11 篇 k. ito
10 篇 korondi péter
10 篇 derong liu
10 篇 xingming fan
10 篇 xin zhang
9 篇 wu min

语言

3,067 篇 英文
44 篇 中文
22 篇 其他

检索条件"任意字段=International Symposium on Computational Intelligence in Robotics and Automation"

共 3103 条记录，以下是391-400 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：

Advances in Autonomous Robotic Grasping: An Overview of Reinforcement Learning Approaches 6

Advances in Autonomous Robotic Grasping: An Overview of Rein...

引用

6th IEEE international symposium on Logistics and Industrial Informatics, LINDI 2024

作者： Farkas, Bálint Károly Galambos, Péter Széll, Károly Óbuda University Alba Regia Faculty SzékesfehérvárH-8000 Hungary Óbuda University Antal Bejczy Center for Intelligent Robotics Budapest Hungary

ISBN: (纸本)9798331516192

Reinforcement Learning (RL) has become a pivotal tool in robotic manipulation, especially for tasks requiring adaptability, such as object grasping. By allowing robots to learn optimal behaviors through trial and error, RL, when integrated with advanced vision systems, enhances the ability of robots to interact effectively with their environment. This paper reviews the fundamental aspects of RL in robotic grasping, including perception, decision-making, and execution, and explores practical applications in frameworks like 'Laboratory automation Plug and Play (LAPP)'. While significant advancements have been made, challenges such as sim-to-real transfer, computational efficiency, and robustness remain critical issues. Additionally, the role of vision systems in object detection and grasp planning is examined, along with the evaluation of performance in simulated and real-world settings. The paper concludes by discussing future directions, emphasizing the need for improved algorithms, better sim-to-real techniques, and multi-agent cooperation. Overall, RL continues to advance autonomous robotic systems, enhancing their precision and capability in complex tasks. © 2024 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Low Cost Point to Point Navigation System

Low Cost Point to Point Navigation System

引用

7th international Conference on automation, robotics and Applications (ICARA)

作者： Spampinato, Giuseppe Bruna, Arcangelo Giacalone, Davide Messina, Giuseppe STMicroelect Syst Res & Applicat Catania Italy

ISBN: (纸本)9781665404693

This document describes a novel low-cost methodology called "Towards and Tangent" for point to point navigation in robotics systems. The system navigates in an unknown environment, and it avoids obstacles to reach the desired point, using only laser range sensor, without any integration with mems or another kind of data. It is composed by two simple steps: head toward the goal and select the direction with the lower angle to overcome the obstacle. In this way, compared to the state of the art algorithms, it requires less computational resources, since it does not need to detect obstacles discontinuities and do not need to follow an obstacle's boundaries. Moreover, a simple state machine can handle both obstacle avoidance and point to point navigation. Even if the system is easy to implement and requires low resources, it reaches high performances, in line with more sophisticated algorithms and works very well in real-time.

关键词： Obstacle avoidance point to point navigation Simultaneous Localization And Mapping (SLAM) robotics

来源：评论

学校读者我要写书评

暂无评论

iHRC: An AR-Based Interface for Intuitive, Interactive and Coordinated Task Sharing Between Humans and Robots in Building Construction 38

iHRC: An AR-Based Interface for Intuitive, Interactive and C...

引用

38th international symposium on automation and robotics in Construction, ISARC 2021

作者： Amtsberg, Felix Yang, Xiliu Skoury, Lior Wagner, Hans Jakob Menges, Achim Institute for Computational Design and Construction University of Stuttgart Germany

ISBN: (纸本)9789526952413

The research presented in this paper introduces a novel method for Augmented Reality informed human-machine collaboration in the context of timber prefabrication. The concept is based on the craftsman controlled instructive interaction between a High Level of automation (robotic) fabrication setup and a human co-worker. It argues that by enabling the craftsmen to coordinate or take over specific process parts, a significant increase in flexibility and robustness of automated workflows becomes feasible. This is highly relevant within the project-based construction industry where efficient and flexible production of one-off components is predominant. A novel approach to integrate human and robotic co-workers in a joint fabrication setup that we call "Instructive Human Robot Collaboration" is introduced. With Vizor, a computational framework was developed for this purpose. It provides an intuitive interface between human and robotic fabrication units via a mixed reality head-mounted display (HMD). Finally, the proposed method is tested with an initial case study in which a 14-Axis fabrication setup is connected with human craft. The HMD gives a craftsman without any knowledge in robot programming direct control over the fabrication setup and extends its individual skill set. Fabrication tasks can be shared freely and between human and robotic units, enabling a dynamically adaptive workflow. © 2021 Proceedings of the international symposium on automation and robotics in Construction. All rights reserved.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Pedestrian Target Detection Model Based on Improved Yolov8

Pedestrian Target Detection Model Based on Improved Yolov8

引用

Artificial intelligence and Electromechanical automation (AIEA), international Conference on

作者： Jinglun Huang Jianan Liang Yongjun Cao School of Electronics and Information Engineering Wuyi University Jiangmen Guangdong China Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent Manufacturing GDAS Guangzhou Guangdong China South China Robotics innovation Research Institute Foshan Guangdong China School of Mechanical & Automotive Engineering South China University of Technology Guangzhou Guangdong China

ISBN: (数字)9798350366174

ISBN: (纸本)9798350366181

Dense pedestrian detection is a key technology in public intelligent surveillance. It identifies the location and number of pedestrians in videos through object detection methods, thereby achieving intelligent surveillance of crowds. However, in crowded scenes, due to occlusion and small pedestrian targets, it is easy to miss pedestrians. To solve this problem, this paper proposes an improved YOLOv8 detection algorithm, YOLOv-8FastTCD. Firstly, the FasterNet module is used to replace the backbone network. Secondly, a task collaborative dynamic detection head (TCDDH) is introduced after the neck network. The performance of this model on the CrowdHuman dense pedestrian detection dataset has been improved, with mAP 50 and $\mathrm{mAP}_{50-95}$ reaching $\mathbf{7 8. 4 \%}$ and 51.5% respectively, which are 2.1% and 2.0% higher than the original YOLOv8n model.

关键词： Performance evaluation Pedestrians Shape computational modeling Surveillance Object detection Real-time systems Neck computational efficiency Videos

来源：评论

学校读者我要写书评

暂无评论

Tiny-YOLOv7: Tiny Object Detection Model for Drone Imagery 12th

Tiny-YOLOv7: Tiny Object Detection Model for Drone Imagery

引用

12th international Conference on Image and Graphics, ICIG 2023

作者： Cheng, Pengchao Tang, Xu Liang, Wenqi Li, Yu Cong, Wei Zang, Chuanzhi School of Artificial Intelligence Shenyang University of Technology Shenyang10142 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China

ISBN: (纸本)9783031463105

With the rapid development of drones, tiny object detection in drone-captured scenarios has become a challenge task. However, the altitude of the drone changes while flying lead to the scale of the object changes dramatically. In addition, drones flying quickly cause motion blur on the densely tiny objects. In order to address the two issues mention above, we propose Tiny-YOLOv7. In order to detect multi-scale objects, we replace the original prediction heads with transformer prediction heads. For the motion blur issue, we propose DBS module to extract more visual elements and maintain computational cost of model. The DBS module consists of Dynamic Region-Aware Convolution (DRConv), Batch Normalization and Silu modules. On scenarios with dense objects, we additionally incorporate the Convolutional Block Attention Model (CBAM) to find the attention region of dense objects. Tiny-YOLOv7 is an effective and elegant method for handing tiny object detection. We validate our model through extensive experiments on VisDrone2021 and DOTA-v1.0 datasets. The results show that our method obtains remarkable improvements over the other models. In VisDrone2021 dataset, the mAP result of our method is 39.22 %, which is higher than SOTA method by 1.07 %. Furthermore, experiments on dataset DOTA-v1.0 demonstrate generalization of the propose model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Automotive Scenarios for Trajectory Tracking using Machine Learning Techniques and Image Processing

Automotive Scenarios for Trajectory Tracking using Machine L...

引用

international symposium on Applied computational intelligence and Informatics ( SACI)

作者： Delia Moga Ioan Filip Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania

This paper presents a study on using innovative machine learning techniques that can be applied in automotive traffic scenarios to increase a vehicle’s level of autonomy. The overtaking traffic scenario is treated for predicting the vehicle trajectory when overtaking another vehicle and the data is obtained by image processing using a video camera. Two different methods are compared, first by using classic tracking methods and a Kalman filter (as an adaptive filter) and second by using a machine learning technique - Support Vector Machine. The present article uses as inputs the data received from the camera and focuses on tracking selected objects and estimating their position using mainly image processing in automotive scenarios. The main purpose of this work is to experiment and compare different tracking modes to determine those that have the best performances in terms of runtime, memory usage and prediction accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Collision-Free MPC for Legged Robots in Static and Dynamic Scenes

Collision-Free MPC for Legged Robots in Static and Dynamic S...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Gaertner, Magnus Bjelonic, Marko Farshidian, Farbod Hutter, Marco Swiss Fed Inst Technol Robot Syst Lab CH-8092 Zurich Switzerland

ISBN: (纸本)9781728190778

We present a model predictive controller (MPC) that automatically discovers collision-free locomotion while simultaneously taking into account the system dynamics, friction constraints, and kinematic limitations. A relaxed barrier function is added to the optimization's cost function, leading to collision avoidance behavior without increasing the problem's computational complexity. Our holistic approach does not require any heuristics and enables legged robots to find whole-body motions in the presence of static and dynamic obstacles. We use a dynamically generated euclidean signed distance field for static collision checking. Collision checking for dynamic obstacles is modeled with moving cylinders, increasing the responsiveness to fast-moving agents. Furthermore, we include a Kalman filter motion prediction for moving obstacles into our receding horizon planning, enabling the robot to anticipate possible future collisions. Our experiments) demonstrate collision-free motions on a quadrupedal robot in challenging indoor environments. The robot handles complex scenes like overhanging obstacles and dynamic agents by exploring motions at the robot's dynamic and kinematic limits.

关键词： Legged locomotion computational modeling Dynamics Kinematics Predictive models Planning Trajectory

来源：评论

学校读者我要写书评

暂无评论

Skills Composition Framework for Reconfigurable Cyber-Physical Production Modules

Skills Composition Framework for Reconfigurable Cyber-Physic...

引用

international Conference on Emerging Technologies and Factory automation (ETFA)

作者： Aleksandr Sidorenko Achim Wagner Martin Ruskowski Innovative Factory System German Research Center for Artificial Intelligence Kaiserslautern Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

While the benefits of reconfigurable manufacturing systems (RMS) are well-known, there are still challenges to their development, including, among others, a modular software architecture that enables rapid reconfiguration without much reprogramming effort. Skill-based engineering improves software modularity and increases the reconfiguration potential of RMS. Nevertheless, a skills' composition framework with a focus on frequent and rapid software changes is still missing. The behavior trees (BTs) framework is a novel approach that enables the intuitive design of modular hierarchical control structures. BTs have been mostly explored from the AI and robotics perspectives, and little work has been done in investigating their potential for composing skills in the manufacturing domain. This paper proposes a framework for skills' composition and execution in skill-based reconfigurable cyber-physical production modules (RCPPMs). It is based on distributed BTs and provides good integration between low-level devices' specific code and AI-based task-oriented frameworks. We have implemented the provided models for the IEC 61499-based distributed automation controllers. This shows the instantiation of the proposed framework with specific industrial technology to enable its evaluation by the automation community.

关键词： Adaptation models Protocols Software architecture computational modeling Production Computer architecture Software Artificial intelligence Robots Manufacturing systems

来源：评论

学校读者我要写书评

暂无评论

Learning Motor Resonance in Human-Human and Human-Robot Interaction with Coupled Dynamical Systems

Learning Motor Resonance in Human-Human and Human-Robot Inte...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Duarte, Nuno Ferreira Rakovic, Mirko Santos-Victor, Jose Univ Lisbon Inst Super Tecn Inst Syst & Robot Lisbon Portugal Univ Novi Sad Fac Tech Sci Novi Sad Serbia

ISBN: (纸本)9781728190778

Human interaction involves very sophisticated non-verbal communication skills like understanding the goals and actions of others and coordinating our own actions accordingly. Neuroscience refers to this mechanism as motor resonance, in the sense that the perception of another persons actions and sensory experiences activates the observer's brain as if (s)he would be performing the same actions and having the same experiences. We analyze and model the non-verbal cues exchanged between two humans in handover actions. The contributions of this paper are the following: (i) computational models, using recorded motion data, describing the motor behaviour of each actor in action-in-interaction situations;(ii) a computational model that captures the behaviour of the "giver" and "receiver" during an object handover action, by coupling the wrist kinematic motion of the actors;and (iii) the transfer of these models to the iCub robot for both action execution and recognition. Our results show that: (i) the robot is able to interpret the human wrist motion and infer whether or not the observed action is an "handover";and (ii) use the motor resonance model to coordinate its actions with the human partner, during handover actions.

关键词： Wrist Couplings Visualization computational modeling Robot kinematics Humanoid robots Handover

来源：评论

学校读者我要写书评

暂无评论

Multi-robot Informative Path Planning using a Leader-Follower Architecture

Multi-robot Informative Path Planning using a Leader-Followe...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Di Caro, Gianni A. Yousaf, Abdul Wahab Ziaullah

ISBN: (纸本)9781728190778

We consider typical scenarios where an autonomous multi-robot team is used for surveying a large region. The desired output is a spatial map of the physical values of interest. Accounting for spatial correlation and uncertainty, the map is modeled using a Gaussian Process. Considering real-world constraints such as limited time budget and collision avoidance, we model team's mission as a joint informative path planning problem which is tackled using a leader-follower architecture balancing centralized and fully distributed computation of plans. The leader first identifies a convex containment region that is to be sampled by the team. Next, through a combination of Bayesian optimization and Monte Carlo simulation, distinct sampling locations are identified and assigned to the followers. Each follower independently solves an orienteering problem to find a collision-free path maximizing information gain. A team-level adaptive replanning criterion is designed to keep redirecting sampling towards the most informative regions. The algorithm has been validated in computational experiments for map estimation. Compared to a baseline reference algorithm, it has shown a significantly higher accuracy. Moreover, the approach has shown good ability to support network connectivity, as well as good scalability in computation.

关键词： Monte Carlo methods Uncertainty computational modeling Scalability Robot kinematics Computer architecture Path planning

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311页 << < 36 37 38 39 40 41 42 43 44 45 > >>

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：