检索结果-内蒙古大学图书馆

International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Rui Liang Kai Wu Sheng Xu Tiantian Xu Xiaoyi Ma Lianyu Fu City West Power Supply Branch State Grid Tianjin Electric Power Company Tianjin China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen China State Grid Tianjin Information & Telecommunication Company Tianjin China

ISBN: (纸本)9781665402460

Angle-of-arrival (AOA) target localization using the unmanned aerial vehicle (UAV) has been widely applied in many practical applications. To localize an invasive target quickly and accurately, both the estimation and UAV path optimization algorithms are required. This paper focuses on developing a path optimization method to improve the target estimation performance. Firstly, the problem formulation of AOA target localization is introduced. Secondly, the classical pseudolinear Kalman filter (PLKF) and the gradient-based path optimization are presented. Thirdly, we analyze the problems that existed in the previous methods and propose an improved gradient-descent path optimization algorithm combined with a simple grid search method. Finally, the simulation examples verify the effectiveness of the proposed methods.

关键词： Location awareness Adaptation models Three-dimensional displays Target tracking Search methods Estimation Optimization methods

来源：评论

学校读者我要写书评

暂无评论

A comprehensive review on developments of synthetic dimensions

arXiv

引用

arXiv 2025年

作者： Yu, Danying Song, Wange Wang, Luojia Srikanth, Rohith Sridhar, Sashank Kaushik Chen, Tao Huang, Chenxi Li, Guangzhen Qiao, Xin Wu, Xiaoxiong Dong, Zhaohui He, Yanyan Xiao, Meng Chen, Xianfeng Dutt, Avik Gadway, Bryce Yuan, Luqi State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and Manipulation Jiangsu Key Laboratory of Artificial Functional Materials College of Engineering and Applied Sciences Nanjing University Nanjing210093 China New Cornerstone Science Laboratory Department of Physics University of Hong Kong Hong Kong Department of Mechanical Engineering Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States Department of Physics University of Illinois at Urbana-Champaign UrbanaIL61801-3080 United States Department of Physics The Pennsylvania State University University ParkPA16802 United States School of Physics Xi’an Jiao Tong University Xi’an710049 China College of Physics and Electronics Engineering Northwest Normal University Lanzhou730070 China Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education School of Physics and Technology Wuhan University Wuhan430072 China Collaborative Innovation Center of Light Manipulations and Applications Shandong Normal University Jinan250358 China at Maryland College ParkMD20742 United States

The concept of synthetic dimensions has emerged as a powerful framework in photonics and atomic physics, enabling the exploration of high-dimensional physics beyond conventional spatial constraints. Originally developed for quantum simulations in high dimensions, synthetic dimensions have since demonstrated advantages in designing novel Hamiltonians and manipulating quantum or optical states for exploring topological physics, and for applications in computing and information processing. Here we provide a comprehensive overview of progress in synthetic dimensions across photonic, atomic, and other physical platforms over the past decade. We showcase different approaches used to construct synthetic dimensions and highlight key physical phenomena enabled by the advantage of such a framework. By offering a unified perspective on developments in this field, we aim to provide insights into how synthetic dimensions can bridge fundamental physics and applied technologies, fostering interdisciplinary engagement in quantum simulation, atomic and photonic engineering, and information processing. © 2025, CC BY.

关键词： Atoms

来源：评论

学校读者我要写书评

暂无评论

A grasping CNN with image segmentation for mobile manipulating robot

A grasping CNN with image segmentation for mobile manipulati...

引用

2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Yu, Yingying Cao, Zhiqiang Liang, Shuang Liu, Zhicheng Yu, Junzhi Chen, Xuechao Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Intelligent Robotics Institute BIT Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China

ISBN: (纸本)9781728163215

This paper presents a grasping convolutional neural network with image segmentation for mobile manipulating robot. The proposed method is cascaded by a feature pyramid network FPN and a grasping network DrGNet. The FPN network combined with point cloud clustering is used to obtain the mask of the target object. Then, the grayscale map and the depth map corresponding to the target object are combined and sent to the DrGNet network for providing multi-scale images. On this basis, depthwise separable convolution is used for encoding. The results of encoders are refined according to the light-weight RefineNet as well as sSE, which can achieve a better grasp detection. The proposed method is verified by the experiments on mobile manipulating robot. © 2019 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Automatic Operating Method of Robot Dexterous Multi-fingered Hand Using Heuristic Rules 4th

Automatic Operating Method of Robot Dexterous Multi-fingered...

引用

4th International Conference on Cognitive systems and Information Processing, ICCSIP 2018

作者： Wang, Wei Zhang, Qiangbing Sun, Zeyuan Chen, Xi Jiang, Zhihong IRI School of Mechatronical Engineering Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robotics and Systems Beijing China

ISBN: (纸本)9789811379826

Automatic grasp planning of robotic hand is always a difficult problem in robotics. Although researchers have developed underactuated hands with less degrees of freedom, automatic grasp planning is still a difficult problem because of the huge number of possible hand configurations. But humans simplify this problem by applying several usual grasp starting postures on most of grasp tasks. In this paper, a method for grasping planning is presented which can use a set of heuristic rules to limit the possibilities of hand configurations. By modeling the object as a set of primitive shapes and applying appropriate grasp starting postures on it, many grasp samples can be generated. And this is the basic content of the heuristic rules. Then, given grasp samples in finite number, a Simulink and Adams co-simulator is built to simulate these discrete grasp samples. The main purpose of the co-simulator is to simulate the dynamic behavior of robotic hand when grasping and measure the grasp quality using force closure and grasp measurement of largest-minimum resisted wrench. Last, a grasp library with force closure grasps is built where all items of grasp are sorted by the function value of grasp measurement. With the library, it’s easy to plan a grasp for certain object by just selecting an appropriate grasp from the library. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Simulink

来源：评论

学校读者我要写书评

暂无评论

A novel multi-scale fourier descriptor based on plane orthogonal vectors for fast shape retrieval

A novel multi-scale fourier descriptor based on plane orthog...

引用

2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Ma, Jiajun Zhu, Jiafeng Liang, Guoyuan Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong Province China

ISBN: (纸本)9781728163215

Shape retrieval is an interesting and challenging issue in computer vision and robot vision. The recent works employing Fourier-based multi-scale descriptors achieve some success in shape retrieval, especially make real-time application possible by improving the efficiency. However, these methods are commonly adopting really complex shape descriptors to present the shape information which is not intuitive enough. In our work, we propose a new Fourier-based method with novel multi-scale descriptor which is a combination of contour feature and regional feature. This novel descriptor has two main characteristics: First, utilize six different invariant signatures which are based on plane orthogonal vectors;Second, leverage multiple scale structures to describe local and global information of shapes. Except the easiness in understanding, this descriptor approach also produces a more distinct topology of shapes than other approaches which means the property of stability on variations, linear or nonlinear. The method is tested on some popular databases that provides a promising retrieval rate(87.46% and 99.27%) with constant time complexity optimization. The results confirm that our method is more capable of representing the topology of shapes than most other methods based on Fourier descriptor. © 2019 IEEE.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Task-space control interface for SoftBank humanoid robots and its human-robot interaction applications

arXiv

引用

arXiv 2020年

作者： Bolotnikova, Anastasia Gergondet, Pierre Tanguy, Arnaud Courtois, Sébastien Kheddar, Abderrahmane SoftBank Robotics Europe Paris France University of Montpellier–CNRS LIRMM Interactive Digital Humans Montpellier France CNRS-AIST Joint Robotics Laboratory IRL 3218 Tsukuba Japan Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

We present an open-source software interface, called mc naoqi, that allows to perform whole-body task-space Quadratic Programming based control, implemented in mc rtc framework, on the SoftBank robotics Europe humanoid robots. We describe the control interface, associated robot description packages, robot modules and sample whole-body controllers. We demonstrate the use of these tools in simulation for a robot interacting with a human model. Finally, we showcase and discuss the use of the developed open-source tools for running the human-robot close contact interaction experiments with real human subjects inspired from assistance scenarios. Copyright © 2020, The Authors. All rights reserved.

关键词： Anthropomorphic robots

来源：评论

学校读者我要写书评

暂无评论

A DRL-based framework for self-balancing exoskeleton walking

A DRL-based framework for self-balancing exoskeleton walking

引用

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

作者： Yao Dong Yong He Xinyu Wu Guangju Gao Wei Feng A Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

Self-balancing exoskeleton is a robot that can be worn by paraplegic patients for walking without external support. The exoskeleton is similar to humanoid robot with two normal human feet, which cause inconvenience to existing control methods. These model-based methods require mathematical modeling and usually do not consider the impact of the controller like limits of position and torque. This paper proposes a deep reinforce learning (DRL) based training framework for self-balancing exoskeleton, for the purpose of learning a feasible walking policy which can generate walk pattern similar to the given reference motion for paraplegia with exoskeleton. The framework is based on policy gradient descent algorithm, and a way to simplify the model is proposed to speed up model training. The experimental results indicate that this training framework which fully considers the controller can acquire a feasible control policy for self-balancing exoskeleton.

关键词： Cows Robots Real-time systems Conferences

来源：评论

学校读者我要写书评

暂无评论

Phase diagram with an antiferroelectric/ferroelectric phase boundary in AgNbO3−LiTaO3 energy-storage ceramics by lattice dynamics and electronic transitions

引用

Physical Review B 2021年第17期104卷 174104-174104页

作者： Kai Dai (戴凯) Anyang Cui (崔安阳) Yan Ye (叶艳) Kai Jiang (姜凯) Jinzhong Zhang (张金中) Yawei Li (李亚巍) Genshui Wang (王根水) Xianlin Dong (董显林) Zhigao Hu (胡志高) Junhao Chu (褚君浩) Technical Center for Multifunctional Magneto-Optical Spectroscopy (Shanghai) Engineering Research Center of Nanophotonics & Advanced Instrument (Ministry of Education) Department of Materials School of Physics and Electronic Science East China Normal University Shanghai 200241 China Key Laboratory of Inorganic Functional Materials and Devices Shanghai Institute of Ceramics Chinese Academy of Sciences Shanghai 200050 China Collaborative Innovation Center of Extreme Optics Shanxi University Taiyuan Shanxi 030006 China Shanghai Institute of Intelligent Electronics & Systems Fudan University Shanghai 200433 China

Here, a phase diagram with phase coexistence near the polycrystalline phase boundary has been studied on (1−x)AgNbO3−xLiTaO3 ceramics by analyzing infrared- (IR) and Raman-active phonon dynamics under tuning chemical component and temperature. Optical dielectric functions, ferroelectric domain, and electronic transitions promote the understanding of lattice structure in AgNbO3, and the antiferroelectric (AFE) to ferroelectric (FE) transformation, which results from the joint effect of the cationic antipolar and the oxygen octahedron distortion. The spectroscopic methods of x-ray diffraction, IR reflection, and Raman scattering reveal the mixed phase boundary at x (LiTaO3) = 0.05, which is the indication of a first-order transition, contributing to the excellent pyroelectric property. Note that the soft mode near 50 cm−1 is sensitive to reveal the lattice transformation. Moreover, the temperature-dependent optical band gap ( Eg ) with the specific electronic transition behavior has been further explored, and becomes complementary evidence for the structural phase transition. This study presents the systematical results on structural properties and optical/dielectric properties for the state-of-the-art AgNbO3 system for designing energy-storage devices.

关键词： Antiferroelectricity Phase transitions Phonons Ferroelectrics Ellipsometry Fourier transform infrared spectroscopy Raman spectroscopy

来源：评论

学校读者我要写书评

暂无评论

A multi-task learning convolutional neural network for object pose estimation

A multi-task learning convolutional neural network for objec...

引用

2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Wang, Yurui Jin, Shaokun Ou, Yongsheng Shenzhen Institutes of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Beijing China University of Chinese Academy of Sciences Beijing China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

ISBN: (纸本)9781728163215

Estimating 6D poses of objects from RGB images is very crucial for robots to interact with the surrounding environment and to cooperate with humans. It is a challenging problem due to the various shapes of objects, the occlusions among objects, as well as the complexity of the scene. In this study, we present a new multi-task convolutional neural network for 6D object pose estimation, which also learns the object region in the image to further improve the estimation result. A weighted loss computed from the training samples is adopted to guarantee that the components of the estimated pose are equally accurate. Additionally, we sythesize new virtual data based on the existing training data so as to overcome the possible adverse situation caused by insufficiency of training data. Experiments on the YCB-video dataset are undertaken to validate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Obstacle avoidance with reinforcement learning and adaptive resonance theory

Obstacle avoidance with reinforcement learning and adaptive ...

引用

2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Ye, Lingjian Zhou, Yimin Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen China

ISBN: (纸本)9781728163215

The reinforcement learning (RL) of the autonomous mobile agent is one of the actual research topics. It permits mobile agents to interact constantly with their environment and to avoid obstacles. First, this paper presents an algorithm which integrates Deep Deterministic Policy Gradient (DDPG) algorithm and Fuzzy Adaptive Resonance Theory (ART) in order to improve generalization performance of RL. Then the curiosity is introduced to integrate with the first proposed algorithm to solve the problem of slow convergence caused by Fuzzy ART. Results of the simulation experiments demonstrate the effectiveness of the proposed algorithm. It shows that the algorithms perform well in both low-dimension and high-dimension state space. © 2019 IEEE.

关键词： Reinforcement learning

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：