检索结果-内蒙古大学图书馆

Chinese control Conference (CCC)

作者： Yaojun Liu Xingwen Liu Nyima Tashi Lab. of Complex Systems & Intelligent Control Key Lab. of Electronic Information of State Ethnic Affairs Commission College of Electrical Engineering Southwest Minzu University Chengdu Sichuan China Engineering Research Center for Tibetan Information Processing School of Information Science and Technology Tibet University Lhasa China

Cooperative behavior has been of great concern in evolutionary game researches because of its important role in social life and natural evolution. Since memory can greatly influence the emergence of cooperative behavior, memory-based research on evolutionary games has proliferated in recent years. In the present paper, inspired by the well-known “Stanford marshmallow experiment” (SME), we proposed a multi-memory mechanism in Snowdrift game (SDG) on spatial lattice networks whose core lies in what follows: Players are divided into two groups according to individual self-control; different memory lengths are set by group and by time in a single realization. The simulation results show that our proposed mechanism promotes cooperation level of the considered evolutionary game. More specifically, as memory length increases to an intermediate length, the cooperation level increases as well. For mechanism with short memory length, the effect of population structure is obvious and small values of adjusting factor can intensively facilitate high-frequency cooperative behavior. These findings may be helpful to understand the connection between population heterogeneity and the emergence of high cooperation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Reinforcement Learning Algorithm for Underwater Environment Search 2

A Reinforcement Learning Algorithm for Underwater Environmen...

引用

2022 2nd International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2022

作者： Xiong, Minglei Xie, Guangming State Key Laboratory for Turbulence and Complex Systems Intelligent Biomimetic Design Lab. College of Engineering Peking University Beijing100871 China Peng Cheng Laboratory Shenzhen518055 China Robot Technology Co. Ltd. Beijing100176 China

ISBN: (纸本)9783800760268

Known as an intelligent learning algorithm that can be employed without any sufficient prior information, the reinforcement learning algorithm has been widely used recently. The underwater unknown 3D environment search is a typical application scenario lacking any prior knowledge. This study proposes an algorithm framework including one agent and an intelligent swarm based on the idea of reinforcement learning. This learning algorithm can be adopted to train only one individual. Many of such individuals will then create an intelligent group which can efficiently and completely search underwater unknown 3D environments. Moreover, the proposed algorithm needs no further prior knowledge of the unknown environment. Even if the algorithm fails to reach the optimal level in the use of reinforcement learning, the results confirm the applicability prospect of reinforcement learning in this field and provide an appealing direction. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

One-Shot Three-Dimensional Measurement Based on Spectral Interferometry Using a Digital Micromirror Device

One-Shot Three-Dimensional Measurement Based on Spectral Int...

引用

Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Jinxu Zhang Liheng Shi Yingying Gu Donglai Zhang Lu Yin Guanhao Wu Department of Precision Instrument State Key Laboratory of Precision Measurement Technology and Instruments Tsinghua University Beijing China Space Optoelectronic Measurement and Perception Lab. Beijing Institute of Control Engineering Beijing China National Key Laboratory of Space Intelligent Control China Academy of Space Technology Beijing China

We present a one-shot 3D spectral interferometry technique using a digital micromirror device. By encoding the distribution of the spatial light field, this approach enables 3D imaging of step structures within 27 ms.

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Optical interferometry Three-dimensional displays Imaging Surface emitting lasers Measurement by laser beam Encoding Microcavities

来源：评论

学校读者我要写书评

暂无评论

Design of Variance-Constrained H∞state Estimation Algorithm for Delayed Memristive Neural Networks with Attacks: An Adaptive Event-Triggered Approach 8

Design of Variance-Constrained H∞State Estimation Algorithm...

引用

8th IEEE International Conference on Cloud Computing and Intelligence systems, CCIS 2022

作者： Gao, Yan Hu, Jun Yu, Hui Jia, Chaoqing Harbin University of Science and Technology Department of Mathematics Harbin150080 China Harbin University of Science and Technology School of Automation Harbin150080 China Harbin University of Science and Technology Heilongjiang Prov. Key Lab. of Optimization Control and Intelligent Analysis for Complex Systems Harbin150080 China

ISBN: (纸本)9781665477352

This paper studies the algorithm design of variance-constrained H∞ state estimation problem for delayed memristive neural networks with adaptive event-triggered mechanism. The denial-of-service attacks are modeled by a series of random variables obeying the Bernoulli distribution with known probability. In addition, the adaptive event-triggered mechanism is introduced into the sensor-to-estimator to avoid unnecessary resource consumption. Our purpose is to construct a finite-horizon state estimation algorithm, and sufficient condition is obtained for the estimation error system satisfying the H∞ performance requirement and the error variance boundedness. Finally, a numerical example is used to illustrate the feasibility of the presented H∞ state estimation algorithm. © 2022 IEEE.

关键词： state estimation

来源：评论

学校读者我要写书评

暂无评论

Marker or Markerless? Mode-Switchable Optical Tactile Sensing for Diverse Robot Tasks

arXiv

引用

arXiv 2024年

作者： Ou, Ni Chen, Zhuo Luo, Shan The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China The Robot Perception Lab. Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom

Optical tactile sensors play a pivotal role in robot perception and manipulation tasks. The membrane of these sensors can be painted with markers or remain markerless, enabling them to function in either marker or markerless mode. However, this uni-modal selection means the sensor is only suitable for either manipulation or perception tasks. While markers are vital for manipulation, they can also obstruct the camera, thereby impeding perception. The dilemma of selecting between marker and markerless modes presents a significant obstacle. To address this issue, we propose a novel mode-switchable optical tactile sensing approach that facilitates transitions between the two modes. The marker-to-markerless transition is achieved through a generative model, whereas its inverse transition is realized using a sparsely supervised regressive model. Our approach allows a single-mode optical sensor to operate effectively in both marker and markerless modes without the need for additional hardware, making it well-suited for both perception and manipulation tasks. Extensive experiments validate the effectiveness of our method. For perception tasks, our approach decreases the number of categories that include misclassified samples by 2 and improves contact area segmentation IoU by 3.53%. For manipulation tasks, our method attains a high success rate of 92.59% in slip detection. Code, dataset and demo videos are availab.e at the project website https://***/Marker-Markerless-Transition/ Copyright © 2024, The Authors. All rights reserved.

关键词： Tactile sensors

来源：评论

学校读者我要写书评

暂无评论

Trajectory Planning for Autonomous Overtaking on Curved Roads with Avoidance of Human Driving Vehicles and Static Obstacles

Trajectory Planning for Autonomous Overtaking on Curved Road...

引用

IEEE International Conference on Unmanned systems (ICUS)

作者： Chen Shao Xuting Duan Jianshan Zhou Dezong Zhao State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle School of Transportation Science and Engineering Beihang University Infrastructure Systems and Safety Control Infrastructure Systems and Safety Control Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Zhongguancun Laboratory School of Transportation Science and Engineering Beihang University Beijing China James Watt School of Engineering University of Glasgow Glasgow U.K

A proposed obstacle avoidance trajectory planning method for autonomous vehicles considers social behavior characteristics to address the interaction problem with human drivers in mixed traffic environments. The method integrates graph theory and centrality functions to classify and predict driver behavior, employing model predictive control (MPC) to plan the autonomous vehicle's trajectory. By combining these social behaviors, the method ensures safe completion of the driving task based on probability. Experimental results from an interactive obstacle avoidance scenario in a curved environment confirm the successful completion of the task, validating the proposed method's feasibility and effectiveness, supporting its potential for real-world application.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deep Domain Adaptation Regression for Force Calibration of Optical Tactile Sensors

Deep Domain Adaptation Regression for Force Calibration of O...

引用

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

作者： Zhuo Chen Ni Ou Jiaqi Jiang Shan Luo Department of Engineering Robot Perception Lab Centre for Robotics Research King’s College London London United Kingdom State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sensors and existing tactile sensors which may have incurred damage or aging. However, the conventional neural-network-based force calibration method necessitates a large volume of force-lab.led tactile images to minimize force prediction errors, with the need for accurate Force/Torque measurement tools as well as a time-consuming data collection process. To address this challenge, we propose a novel deep domain-adaptation force calibration method, designed to transfer the force prediction ability from a calibrated optical tactile sensor to uncalibrated ones with various combinations of domain gaps, including marker presence, illumination condition, and elastomer modulus. Experimental results show the effectiveness of the proposed unsupervised force calibration method, with lowest force prediction errors of 0.102N (3.4% in full force range) for normal force, and 0.095N (6.3%) and 0.062N (4.1%) for shear forces along the x-axis and y-axis, respectively. This study presents a promising, general force calibration methodology for optical tactile sensors.

关键词： Accuracy Force Tactile sensors Lighting Elastomers Data collection Optical imaging Adaptive optics Calibration Optical sensors

来源：评论

学校读者我要写书评

暂无评论

An Optimal control Based Trajectory Planning Method for Cooperative Merging Maneuvers

An Optimal Control Based Trajectory Planning Method for Coop...

引用

intelligent Robotics and systems (ISoIRS), International Symposium on

作者： Qi Wang Hao Ge Xuting Duan Jianshan Zhou State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control State Key Laboratory of Air Traffic Management System and Technology School of Transportation Science and Engineering Beihang University Beijing China State Key Laboratory of Air Traffic Management System and Technology Nanjing Research Institute of Electronic Engineering Nanjing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China

Due to the prediction errors and diverse driving styles of surrounding vehicles, traffic congestion and even accidents can occur in the traffic bottleneck area where vehicles merge into the main road. To ensure that connected and automated vehicles (CAVs) can quickly and efficiently merge into the main road, this paper proposes a cooperative trajectory planning method based on optimal control for vehicle cut-in scenarios. A optimal control model is constructed, and a quintic polynomial is used to generate the initial solution of the optimal control problem to accelerate the solution process and improve the success rate. Finally, The obtained merging trajectory is then synchronized with the movement of vehicles on the main road to optimize their actions and ensure a safe merging process. Joint simulation with Robot Operating System (ROS) and RVIZ is utilized, and the results show that the proposed algorithm can quickly obtain cooperative results, the locally successful merging trajectory meets the requirements of smoothness and safety, and if the solution does not allow merging, the merging vehicle is instructed to terminate the execution.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

引用

IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel state Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collab.rative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

来源：评论

学校读者我要写书评

暂无评论

Multi-Destination Cooperative Task Offloading in Blockchain-Based Vehicular Edge Computing Networks

Multi-Destination Cooperative Task Offloading in Blockchain-...

引用

IEEE International Conference on Unmanned systems (ICUS)

作者： Ping Lang Daxin Tian Xuting Duan Jianshan Zhou State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China

As a novel computing paradigm, the Vehicular Edge Computing (VEC) network provides an additional avenue for onboard task execution for connected and automated vehicles (CAVs) in unmanned systems. In a VEC network, CAVs can offload tasks to different external servers for execution and obtain results. However, existing task offloading studies only focus on the one-to-one offloading of onboard tasks to edge servers, ignoring the requirements of parallel task execution and security. In this paper, we propose a blockchain-based multi-destination cooperative task offloading architecture in a VEC network. Based on this architecture, we analyze the task offloading and blockchain models and formulate a multi-destination cooperative task offloading optimization problem. Finally, we compare the performance of different multi-destination task offloading methods in simulations and demonstrate the effectiveness of the proposed architecture and optimization.

关键词：

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：