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Pick-up strategies for and electrical characterization of ZnO nanowires with a SEM-based nanomanipulator

Nanotechnology and Precision engineering 2023年第1期6卷 26-31页

作者： Mei Liu Lingdi Kong Weilin Su Aristide Djoulde Kai Cheng Jinbo Chen Jinjun Rao Zhiming Wang Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and AutomationShanghai UniversityShanghai 200444China Guangdong Key Laboratory of Fuel Cell Technology School of Chemistry and Chemical EngineeringSouth China University of TechnologyGuangzhou 510640China

Because of their unique mechanical and electrical properties,zinc oxide(ZnO)nanowires are used widely in microscopic and nanoscopic devices and structures,but characterizing them remains *** this paper,two pick-up strategies are proposed for characterizing the electrical properties of ZnO nanowires using SEM equipped with a *** pick up nanowires efficiently,direct sampling is compared with electrification fusing,and experiments show that direct sampling is more stable while electrification fusing is more *** nanowires have cut-off properties,and good Schottky contact with the tungsten probes was *** piezoelectric experiments,the maximum piezoelectric voltage generated by an individual ZnO nanowire was 0.07 V,and its impedance decreased with increasing input signal frequency until it became *** work offers a technical reference for the pick-up and construction of nanomaterials and nanogeneration technology.

关键词： ZnO nanowires nanomanipulator picking up strategy piezoelectric properties electrical characterization

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Offline Palletizing Research Based on Greedy Tabu Search Algorithm 14th

Offline Palletizing Research Based on Greedy Tabu Search Alg...

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14th International Workshop of Advanced Manufacturing and automation, IWAMA 2024

作者： Zhang, Linjun Zhou, Chuanhong Chen, Yuan School of Automation and Mechanical Engineering Shanghai University Shanghai200072 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai200072 China

ISBN: (纸本)9789819626243

This paper implements a greedy tabu search algorithm to deal with the offline palletizing problem, and proposes a two-phase greedy tabu search algorithm. In the first phase, a greedy stochastic adaptive search algorithm is utilized to obtain the local optimal solution of the palletizing problem in the construction process and the local search process, which includes the residual space strategy and the combination of the cargo block strategy, as well as the optimization of the space utilization rate by using the tiling wall strategy. In the second stage, the local optimal solution obtained in the first stage is used as the initial solution, and the tabu search algorithm is used to record the history information of the solution through the tabu table to prevent the algorithm from falling into the local optimal solution, so as to dig deeper into the global optimal solution. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimization algorithms

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Research on 3D Model Classification and Retrieval Based on Graph Convolutional Neural Network 14th

Research on 3D Model Classification and Retrieval Based on G...

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14th International Workshop of Advanced Manufacturing and automation, IWAMA 2024

作者： Deng, Junqiang Zhou, Chuanhong Chen, Xi School of Automation and Mechanical Engineering Shanghai University Shanghai200072 China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai200072 China

ISBN: (纸本)9789819626243

With the popularization of CAD technology in the manufacturing industry, the number of 3D models in the industry is rapidly expanding and becoming increasingly complex. These models carry the intelligence of designers and are highly reusable in the product development process. Manufacturing practitioners realize that they can accelerate product development by reusing the structure of previously designed models. Today, many open-source and private model databases have emerged, but efficient and accurate retrieval of 3D models is still an urgent problem. Current mainstream 3D model classification and retrieval algorithms commonly use deep learning techniques, which can usually be subdivided into voxel-based, point cloud-based and view-based methods. However, they all have their own shortcomings. Therefore, in this paper, we propose a 3D model classification and retrieval algorithm based on graph convolutional neural network for feature extraction of STEP files, which improves the efficiency and accuracy of 3D model classification and retrieval. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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T-Bot: A Programmable Platform for Morphogenesis in Robot Swarms

T-Bot: A Programmable Platform for Morphogenesis in Robot Sw...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Wang, Yu Pan, Mengyun Qin, Xiaoyang Hao, Lina Yang, Yongliang Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China

ISBN: (纸本)9781665481090

The field of robotic self-organizing morphogenesis has traditionally relied on sensing and feedback mechanisms, limiting the robustness of robotic systems in dynamic environments. Recently, the swarms of robots with minimum computational and perceptional capabilities have been developed to achieve global morphogenesis through physical interactions among robots. The automation level of these systems, however, is still limited. Here, we developed the T-bot platform, which is capable of automatic programming. The T-bot system adopts a rule-based control strategy utilizing programmable, automatically switched magnetic shells. These shells mimic differences in cell adhesion by altering the magnetic distribution along the shell, achieving morphogenesis without external sensors or feedback mechanisms. This design improves the robustness of the robotic system. The T-bot assembles pieces to form specific shapes and automatically adjusts its morphology according to task requirements. The T-bot system demonstrates morphogenesis by transitioning between predefined shapes and maintaining effectiveness even when some components fail. The successful application of DAH-inspired programmable magnetic shells opens new avenues for the design of intelligent robotic systems, potentially transforming their applications in various dynamic and unpredictable environments. © 2024 IEEE.

关键词： Cell adhesion

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Gait Generation for the Multi-legged Robot with Injured Legs 41

Gait Generation for the Multi-legged Robot with Injured Legs

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第41届中国控制会议

作者： Ming Zeng Zhijing Wang Yu Ma Jiazhe Liu Baofeng Zhang Yunke Nie Institute of Robotics and Automation Systems School of Electrical and Information EngineeringTianjin University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

When multi-legged robots work in dangerous and complex environments,their legs are easily damaged,resulting in a sharp decline in their movement ability,or even completely out of *** this paper,the gait generation method combined deep reinforcement learning with bionic gait restrictions is presented for multi-legged robots with injured *** this study,we first built an ant gait video acquisition platform using the Camponotus Japonicus as the research object,and on this basis established a gait dataset of injured ***,the gait characteristics of ants in the injured state were ***,our proposed gait generation method combining bionic gait constraints with deep reinforcement learning was compared with the reinforcement-learning-based method in the MATLAB simulation *** test results show that the training reward values of our proposed algorithm are 1-2 times higher than those of the reinforcement learning method alone,and at the same time,the moving speed of the injured robot is also nearly twice as fast.

关键词： Injured multi-legged robot,Ant gait,Gait generation,Reinforcement learning Bionic constraints

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Strain sensor on a chip for quantifying the magnitudes of tensile stress on cells

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Microsystems & Nanoengineering 2024年第3期10卷 305-315页

作者： Yuyin Zhang Yue Wang Hongze Yin Jiahao Wang Na Liu Songyi Zhong Long Li Quan Zhang Tao Yue School of Mechatronics Engineering and Automation Shanghai UniversityShanghaiChina School of Future Technology Shanghai UniversityShanghaiChina Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhouChina Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai UniversityShanghaiChina Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghaiChina

During cardiac development,mechanotransduction from the in vivo microenvironment modulates cardiomyocyte growth in terms of the number,area,and arrangement ***,the response of cells to different degrees of mechanical stimuli is ***-on-a-chip,as a platform for investigating mechanical stress stimuli in cellular mimicry of the in vivo microenvironment,is limited by the lack of ability to accurately quantify externally induced ***,previous technology lacks the integration of external stimuli and feedback sensors in microfluidic platforms to obtain and apply precise amounts of external ***,we designed a cell stretching platform with an in-situ *** in-situ liquid metal sensors can accurately measure the mechanical stimulation caused by the deformation of the vacuum cavity exerted on *** platform was applied to human cardiomyocytes(AC16)under cyclic strain(5%,10%,15%,20 and 25%),and we found that cyclic strain promoted cell growth induced the arrangement of cells on the membrane to gradually unify,and stabilized the cells at 15%amplitude,which was even more effective after 3 days of *** platform’s precise control and measurement of mechanical forces can be used to establish more accurate in vitro microenvironmental models for disease modeling and therapeutic research.

关键词： stress deformation arrangement

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An Improved Object Detection Algorithm for Assembly Line Garbage Sorting 41

An Improved Object Detection Algorithm for Assembly Line Gar...

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第41届中国控制会议

作者： Ming Zeng Jiazhe Liu Xiangzhe Lu Zhijing Wang Yuanhao Li Siying Li Institute of Robotics and Automation Systems School of Electrical and Information EngineeringTianjin University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Garbage object detection is of central importance to achieve accurate garbage *** this work,we propose an improved object detection algorithm for sorting complex garbage objects on the assembly *** algorithm utilizes the Faster RCNN as the baseline and improves its performance with several tips,including deformable convolution,PAFPN,mixup,cutout,color jitter,multi-scale training and ImageNet transfer *** the lack of public datasets for the garbage object detection task,we synthesize a highly realistic multi-object garbage detection dataset,M-GarbageNet,with 20000 training images,5000 validation images and 5000 test ***,we evaluate our algorithm than Faster RCNN,and obtain a 8.2%relative improvement on the M-GarbageNet dataset.

关键词： Garbage object detection Improved Faster RCNN M-GarbageNet Image augmentation

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Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1080-1099页

作者： Mai, Weijian Zhang, Jian Fang, Pengfei Zhang, Zhijun South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Southeast University School of Computer Science and Engineering Nanjing210096 China South China University of Technology Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering Guangzhou510640 China Institute for Super Robotics Huangpu Guangzhou510555 China Nanchang University Jiangxi Thousand Talents Plan Nanchang330031 China Jishou University College of Computer Science and Engineering Jishou416000 China Guangdong Artificial Intelligence and Digital Economy Laboratory Pazhou Lab Guangzhou510335 China Shaanxi University of Technology Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Hanzhong723001 China Changsha Normal University School of Information Science and Engineering Changsha410100 China Guangdong University of Petrochemical Technology School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Maoming525000 China

In the era of artificial intelligence generated content (AIGC), conditional multimodal synthesis technologies (e.g., text-to-image) are dynamically reshaping the natural content. Brain signals, serving as potential reflections of how the brain interprets external information, exhibit a distinctive one-to-many correspondence with various external modalities. This correspondence makes brain signals emerge as a promising guiding condition for multimodal synthesis (e.g., image, text, and audio), which is crucial for developing practical brain–computer interface systems and unraveling complex mechanisms underlying human perception. This survey comprehensively examines the emerging field of brain-conditional multimodal synthesis, termed AIGC-brain, to delineate the current landscape and future directions. To begin, related neuroimaging datasets and generative models are introduced as the foundation of AIGC-brain decoding and analysis. Next, we present a comprehensive taxonomy according to AIGC-brain methodologies, followed by task-specific representative work and implementation details to facilitate in-depth comparison and analysis. Quality assessments are then introduced for both qualitative and quantitative evaluation. Finally, this survey explores insights gained, outlining current challenges and prospects of AIGC-brain. As a pioneering survey, this article paves the way for future advances in AIGC-brain research. © 2020 IEEE.

关键词： Taxonomies

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Correcting of the unexpected localization measurement for indoor automatic mobile robot transportation based on a neural network

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Transportation Safety and Environment 2024年第2期6卷 24-35页

作者： Jiahao Huang Steffen Jung inger Hui Liu Kerstin Thurow Center for Life Science Automation(CELISCA) University of RostockRostock 18119Germany Institute of Automation University of RostockRostock 18119Germany Institute of Artificial Intelligence&Robotics(IAIR) School of Traffic&Transportation EngineeringCentral South UniversityChangsha 410075HunanChina

The increasing use of mobile robots in laboratory settings has led to a higher degree of laboratory ***,when mobile robots move in laboratory environments,mechanical errors,environmental disturbances and signal interruptions are *** can compromise the accuracy of the robot’s localization,which is crucial for the safety of staff,robots and the laboratory.A novel time-series predicting model based on the data processing method is proposed to handle the unexpected localization measurement of mobile robots in laboratory *** proposed model serves as an auxiliary localization system that can accurately correct unexpected localization errors by relying solely on the historical data of mobile *** experimental results demonstrate the effectiveness of this proposed method.

关键词： mobile robots laboratory automation indoor localization neural network

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Nondestructive Testing of Bridge Stay Cable Surface Defects Based on Computer Vision

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Computers, Materials & Continua 2023年第4期75卷 2209-2226页

作者： Fengyu Xu Masoud Kalantari Bangjian Li Xingsong Wang Jiangsu Engineering Lab for IOT Intelligent Robots(IOTRobot) College of AutomationNanjing University of Posts and TelecommunicationsNanjing210023China School of Mechanical Engineering Southeast University Nanjing210096China Rubic Robotics Company AlbertaCanada

The automatically defect detection method using vision inspectionis a promising direction. In this paper, an efficient defect detection method fordetecting surface damage to cables on a cable-stayed bridge automatically isdeveloped. A mechanism design method for the protective layer of cables of abridge based on vision inspection and diameter measurement is proposed bycombining computer vision and diameter measurement techniques. A detectionsystem for the surface damages of cables is de-signed. Images of cablesurfaces are then enhanced and subjected to threshold segmentation by utilizingthe improved local grey contrast enhancement method and the improvedmaximum correlation method. Afterwards, the data obtained through diametermeasurement are mined by employing the moving average method. Imageenhancement, threshold segmentation, and diameter measurement methodsare separately validated experimentally. The experimental test results showthat the system delivers recall ratios for type-I and II surface defects of cablesreaching 80.4% and 85.2% respectively, which accurately detects bulges oncable surfaces.

关键词： Defect detection computer vision bridge cable image enhancement

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