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检索条件"机构=Advanced Robotics and Intelligent Systems laboratory"
374 条 记 录,以下是1-10 订阅
排序:
Automatic Control of Magnetic Helical Microrobots Docking with Target Objects in Liquid Environments
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Journal of Bionic Engineering 2025年 第2期22卷 574-584页
作者: Fu Zhao Haoran Rong Lefeng Wang State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin150080China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of EducationHarbin University of Science and TechnologyHarbin150080China
Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for ... 详细信息
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Integrated Cross-Scale Manipulation and Modulable Encapsulation of Cell-Laden Hydrogel for Constructing Tissue-Mimicking Microstructures
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Research 2025年 第1期2024卷 704-717页
作者: Yanfeng Zhao Xinyi Dong Yang Li Juan Cui Qing Shi Hen-Wei Huang Qiang Huang Huaping Wang Intelligent Robotics Institute School of Mechatronical EngineeringBeijing Institute of TechnologyBeijing 100081China Peking University First Hospital Xicheng DistrictBeijing 100034China Key Laboratory of Instrumentation Science and Dynamic Measurement Ministry of EducationNorth University of ChinaTaiyuan 030051China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Laboratory for Translational Engineering Harvard Medical SchoolCambridgeMA 02139USA Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of EducationBeijing 100081China
Engineered microstructures that mimic in vivo tissues have demonstrated great potential for applications in regenerative medicine,drug screening,and cell behavior ***,current methods for engineering microstructures th... 详细信息
来源: 评论
Evolution Design Methodology of the Metamorphic Mechanisms Inspired by Gene Deduction
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Journal of Mechanical Design 2025年 第8期147卷 083302页
作者: Zhang, Yang Xu, Peng Li, Bing Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robots Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong School of Robotics and Advanced Manufacture Harbin Institute of Technology Shenzhen 518052 China
This article proposes an evolutionary design method for metamorphic mechanisms inspired by gene deduction. First, the correlations between biological evolution and mechanical evolution, biological systems and mechanic... 详细信息
来源: 评论
Dual-modal Motion of Magnetically Controlled Soft Microrobots with Environmentally Responsive Reversible Deformation  24
Dual-modal Motion of Magnetically Controlled Soft Microrobot...
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2nd International Conference on Frontiers of intelligent Manufacturing and Automation, CFIMA 2024
作者: Xin, Zhengyuan Wu, Anping Bai, Kailun Yang, Haotian Lin, Kaijun Shi, Qing Wang, Huaping Hou, Yaozhen Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China School of Medical Technology Beijing Institute of Technology Beijing China Science and Technology on Space Physics Laboratory Beijing China School of Mechatronical Engineering Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China
Soft microrobots have garnered attention in the biomedical field due to their ability to access hard-to-reach regions within living organisms for precise manipulation. However, the inability to alter the stable morpho... 详细信息
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Formation Control of Unmanned Underwater Vehicles With Unknown Absolute Position Using Rigid Graph-Based MPC
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IEEE Internet of Things Journal 2025年
作者: Fu, Bowen Zhu, Daqi Chen, Mingzhi Yang, Simon X. University of Shanghai for Science and Technology Shanghai200093 China University of Guelph Advanced Robotics and Intelligent Systems Laboratory School of Engineering GuelphONN1G2W1 Canada
Formation control of unmanned underwater vehicles (UUVs) is of great significance to the Internet of Underwater Things (IoUT). Currently, various methods are employed for UUV formation control. Among them, rigid graph... 详细信息
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Comprehensive Performance Optimization of a Novel Anthropomorphic Dexterous Hand
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IEEE robotics and Automation Letters 2025年 第7期10卷 6816-6823页
作者: Yifan Ma Weiwei Shang Fei Zhang Shunxiang Pang Shuqing Dai Zhengkun Yi Guotao Li Shuang Cong Department of Automation University of Science and Technology of China Hefei China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China
Grasp and in-hand manipulation of dexterous hands are essential for daily operational tasks. In this study, an optimized design method for a novel anthropomorphic dexterous hand is proposed, which improves the compreh... 详细信息
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Multi-AUV SOM task allocation algorithm considering initial orientation and ocean current environment
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Frontiers of Information Technology & Electronic Engineering 2019年 第3期20卷 330-341页
作者: Da-qi ZHU Yun QU Simon X.YANG Laboratory of Underwater Vehicles and Intelligent Systems Shanghai Maritime University Advanced Robotics and Intelligent Systems Laboratory University of Guelph
There is an ocean current in the actual underwater working environment. An improved self-organizing neural network task allocation model of multiple autonomous underwater vehicles(AUVs) is proposed for a three-dimensi... 详细信息
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Obstacle-Avoidance Motion Planning Method of Manipulator Based on Deep Reinforcement Learning
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Unmanned systems 2025年
作者: Liu, Yiyang Wu, Defan Fu, Yukai Bai, Hongfei Deng, Chao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems 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 Institute of Advanced Technology Nanjing University of Posts and Telecommunications Nanjing210023 China
In recent years, driven by the rapid advancement of industrial automation and intelligent manufacturing, the demand for manipulators to perform tasks in complex environments has significantly increased. Traditional mo... 详细信息
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Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting
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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 cum... 详细信息
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PTRL: Prior Transfer Deep Reinforcement Learning for Legged Robots Locomotion
arXiv
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arXiv 2025年
作者: Huang, Haodong Sun, Shilong Zhao, Zida Huang, Hailin Shen, Changqing Xu, Wenfu School of Robotics and Advanced Manufacturing Harbin Institute of Technology Shenzhen518055 China School of Rail Transportation Soochow University Suzhou215006 China Suzhou Boyata Industrial Internet Company Ltd. Suzhou215100 China Key University Laboratory of Mechanism and Machine Theory and Intelligent Unmanned Systems of Guangdong Guangdong Shenzhen518055 China
In the field of legged robot motion control, reinforcement learning (RL) holds great promise but faces two major challenges: high computational cost for training individual robots and poor generalization of trained mo... 详细信息
来源: 评论