检索结果-内蒙古大学图书馆

Recent advances on monolithic perovskite-organic tandem solar cells

Interdisciplinary Materials 2024年第1期3卷 113-132页

作者： Guanshui Xie Huan Li Longbin Qiu Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Department of Mechanical and Energy EngineeringSUSTech Energy Institute for Carbon NeutralitySouthern University of Science and TechnologyShenzhenChina

Perovskite-organic tandem solar cells(TSCs)have emerged as a groundbreaking technology in the realm of photovoltaics,showcasing remarkable enhancements in efficiency and significant potential for practical ***-organic TSCs also exhibit facile fabrication surpassing that of all-perovskite or all-organic TSCs,attributing to the advantageous utilization of orthogonal solvents enabling sequential solution process for each *** perovskite-organic TSCs capitalize on the complementary light absorption characteristics of perovskite and organic *** is a promising prospect of achieving further enhanced power conversion efficiencies by covering a broad range of the solar spectrum with optimized perovskite absorber,organic semiconductors as well as the interconnecting layer's optical and electrical *** review comprehensively analyzes the recent advancements in perovskite-organic TSCs,highlighting the synergistic effects of combining perovskite with a low open-circuit voltage deficit,organic materials with broader light absorption,and interconnecting layers with reduced optical and electrical ***,the underlying device architecture design,regulation strategies,and key challenges facing the high performance of the perovskite-organic TSCs are also discussed.

关键词： interconnecting layer narrow‐bandgap organic solar cells recombination layer tandem solar cells wide‐bandgap perovskite solar cells

来源：评论

学校读者我要写书评

暂无评论

Adaptive Soft Pneumatic Robot Inspired by Locomotion of Snake

Adaptive Soft Pneumatic Robot Inspired by Locomotion of Snak...

引用

2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Lu, Jinxuan Hu, Xinshu Zhu, Xiaoyu Chen, Cheng Wang, Hongqiang Southern University of Science and Technology Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Shenzhen China Southern University of Science and Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering and Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities Shenzhen China Guangzhou China

ISBN: (纸本)9781665481090

Pneumatic soft robots have garnered widespread attention for their flexibility and adaptability in various applications. However, existing soft robots generally struggle to effectively navigate diverse terrains, especially when it comes to climbing obstacles. This paper introduces an adaptive pneumatic soft robot designed based on snake-like locomotion, which effectively addresses this issue. The robot utilizes four corrugated tubes as its soft actuators, complemented by silicone-made feet with bidirectional friction anisotropy, enabling it to adapt to various terrains and exhibit climbing capabilities. Experiments demonstrate that the robot can traverse different surfaces such as sand, gravel, and slopes, and can climb obstacles up to 20 centimeters high. Additionally, it features a self-regulation mechanism that allows it to recover from accidental overturns. This study presents a soft robot design with multi-terrain adaptability and self-recovery capabilities. © 2024 IEEE.

关键词： Pneumatics

来源：评论

学校读者我要写书评

暂无评论

A practical PID variable stiffness control and its enhancement for compliant force-tracking interactions with unknown environments

引用

science China(Technological sciences) 2023年第10期66卷 2882-2896页

作者： ZHANG Xin ZHOU Hao LIU JinGuo JU ZhaoJie LENG YuQuan YANG ChenGuang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China School of Computing University of PortsmouthPortsmouth PO13HEUK Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhen 518055China Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and EngineeringSouth China University of TechnologyGuangzhou 510640China

Compliant interaction control is a key technology for robots performing contact-rich manipulation *** design of the compliant controller needs to consider the robot hardware because complex control algorithms may not be compatible with the hardware performance,especially for some industrial robots with low bandwidth *** paper focuses on effective and easy-to-use compliant control algorithms for position/velocity-controlled *** by human arm stiffness adaptation behavior,a novel variable target stiffness(NVTS)admittance control strategy is proposed for adaptive force tracking,in which a proportional integral derivative(PID)variable stiffness law is designed to update the stiffness coefficient of the admittance function by the force and position ***,its stability and force-tracking capability are theoretically *** addition,an impact compensator(Impc)is integrated into the NVTS controller to enhance its disturbance-suppression capability when the robot is subjected to strong vibration disturbances in complicated surface polishing *** proposed controllers are validated through four groups of experimental tests using different robots and the corresponding results demonstrate that they have high-accuracy tracking capability and strong adaptability in unknown environments.

关键词： compliant interaction control force tracking PID variable stiffness impact compensator unknown environments

来源：评论

学校读者我要写书评

暂无评论

Pipe-finder: Adaptive, Lightweight Pipe Robot Integrating Origami Anisotropic Stiffness Structure

Pipe-finder: Adaptive, Lightweight Pipe Robot Integrating Or...

引用

2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Chen, Yifei Yang, Deyu Liu, Ziyu Yang, Boyu Wang, Hongqiang Southern University of Science and Technology Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Shenzhen518055 China Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China Southern Marine Science and Engineering Guangdong Laboratory Guangzhou510000 China

ISBN: (纸本)9798350325706

Pipeline inspection poses challenges that require robots to navigate complex environments. However, existing pipeline robots with the rigid bodies often face limitations in terms of efficiency, flexibility, and adaptability considering the significant size variations and complex terrains in pipelines. This paper introduces a novel design of wheel pipeline robots that addresses these limitations by incorporating the Origami Anisotropic Stiffness Structure (OASS). Inspired by the desert iguana's skin, the OASS offers a unique combination of rigidity and flexibility in different directions, making it an ideal skeletal framework for the robot with only 146 g weight. By integrating the OASS with PLA and resin materials, we enhance the robot's support and enable it to effectively navigate diverse pipeline configurations. Experimental results demonstrate the robot's capability to maneuver through pipelines of different diameters, U-shaped turns, obstacles, and even vertical sections. This research provides a promising solution for inspection tasks in complex pipeline systems. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Lidar-Inertial and Downward Vision Based Mobile Robot SLAM in Digital Workshops 13

Lidar-Inertial and Downward Vision Based Mobile Robot SLAM i...

引用

13th IEEE Data Driven Control and Learning systems Conference, DDCLS 2024

作者： Zhang, Yanchao Geng, Hao Liu, Bin Zhang, Yinlong Yuan, Xudong Zhang, Sichao School of Information Science and Engineering Shenyang University of Technology Shenyang110020 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350361674

In order to solve the problems of long-term cumulative error and the absence of absolute pose in the existing Lidar-Inertial Measurement Unit (IMU) fusion methods for Automated Guided Vehicle (AGV) Simultaneous Localization and Mapping (SLAM), we propose a new SLAM method for mobile robot, integrating Lidar, IMU, and a downward vision camera. Firstly, we tightly couple Lidar-IMU and downward vision camera using a multimodal fusion framework. Downward visual measurements are integrated as QR factors into the factor graph, providing absolute pose information to correct cumulative error in the Lidar-IMU system and enable the joint pose estimation of the AGV. Secondly, an enhanced Iterative Closest Point (ICP) point cloud matching algorithm has been developed to correct the incorrect pose. This approach achieves Scan-to-Map alignment by employing a coarse-to-fine matching strategy, thereby enhancing the accuracy of point cloud alignment. Finally, the extended Kalman filter is used to optimize the Lidar pose drift, as well as the Lidar mapping effectively by using the Lidar-IMU as the measurements and the downward visual measurements as the updates. The algorithm has been extensively evaluated on the developed AGV experimental platform. The experimental results show that the position error is less than 0.02 meters and the orientation error is less than 1°, which solves the problems of long-term error accumulation and the lack of absolute pose information for AGV navigation. © 2024 IEEE.

关键词： Extended Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Adaptive Soft Pneumatic Robot Inspired by Locomotion of Snake

Adaptive Soft Pneumatic Robot Inspired by Locomotion of Snak...

引用

IEEE International Conference on robotics and Biomimetics

作者： Jinxuan Lu Xinshu Hu Xiaoyu Zhu Cheng Chen Hongqiang Wang Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Southern University of Science and Technology Shenzhen China Department of Mechanical and Energy Engineering and Guangdong Provincial Key Laboratory of Human Augmentation and Rehabilitation Robotics in Universities Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology Shenzhen China Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) Guangzhou China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

关键词： Corrugated surfaces Actuators Anisotropic magnetoresistance Navigation Friction Biomimetics MIMICs Soft robotics Pneumatic systems Environmental monitoring

来源：评论

学校读者我要写书评

暂无评论

Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells 32

Application of Deep Learning Method to Estimate Bottomhole P...

引用

32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Cheng, Haibo Li, Shichao Zeng, Peng Vyatkin, Valeriy State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Luleå University of Technology Electrical and Space Engineering Department of Computer Science Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350399714

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry. © 2023 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

引用

Journal of Bionic engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

来源：评论

学校读者我要写书评

暂无评论

Identification of PMSM Moment of Inertia based on Model Reference Adaptive Algorithm 4

Identification of PMSM Moment of Inertia based on Model Refe...

引用

4th IEEE International Conference on Power, intelligent Computing and systems, ICPICS 2022

作者： Ding, Fan Zhang, Tao Jia, Danping Zhang, Hualiang Pei, Quanshen Huang, Haoran School of Information Science and Engineering Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology Dalian China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

A method that can identify the rotational inertia in a timely manner is proposed because the performance of a permanent magnet synchronous motor servo system is easily affected by the rotational inertia. Firstly, principles of model-referenced adaptive recognition algorithm is introduced, and the influence of the adaptive gain on the identification results is analyzed. Then, design a suitable range of adaptive gain value, use the set error value to compare the identification error with the set value, and then select the appropriate gain for identification. Finally, through simulation verification, this method has fast identification convergence speed, high precision and strong anti-disturbance. © 2022 IEEE.

关键词： Adaptive algorithms

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data 49

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

引用

49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Cheng, Haibo He, Yunpeng Zeng, Peng Li, Shichao Vyatkin, Valeriy Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350331820

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction. © 2023 IEEE.

关键词： Forecasting

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：