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第35届中国控制与决策会议

作者： Xining Cui Menghui Yu LinQigao Wu Caiqi Wang Yi Xiong Shiqian Wu Institute of Robotics and Intelligent Systems School of Information Science and Engineering Wuhan University of Science and Technology

With the development of computer-related technologies,robot technology and machine vision technology have also been greatly *** intelligent sorting system composed of traditional robots and machine vision can not only reduce production costs,but also improve the efficiency and accuracy of sorting *** these advantages,the machine sorting system is gradually replacing the manual sorting *** develops in the direction of networking,automation,collaboration and intelligence,and has extremely broad development ***,this paper discusses and analyzes the composition,classification and application of the intelligent sorting system in detail,and expounds the key *** the same time,the intelligent sorting system proposed in this paper is ***,the current development of intelligent sorting system is summarized,and the future development trend is prospected.

关键词： robotic technology machine vision intelligent sorting systems

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Hierarchical Multiview Top-k Pooling with Deep-Q-Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 2985-2996页

作者： Li, Zhi-Peng Su, Hai-Long Wu, Yong- Zhang, Qin-Hu Yuan, Chang-An Gribova, Valeriya Filaretov, Vladimir Fedorovich Huang, De-Shuang Eastern Institute of Technology Zhejiang Ningbo315201 China University of Science and Technology of China School of Life Sciences Anhui Hefei230026 China Tongji University Institute of Machine Learning and Systems Biology School of Electronics and Information Engineering Shanghai201804 China Guangxi Academy of Sciences Institute of Big Data and Intelligent Computing Research Center Nanning530007 China Far Eastern Branch of the Russian Academy of Sciences Institute of Automation and Control Processes Vladivostok690041 Russia

Graph neural networks (GNNs) are extensions of deep neural networks to graph-structured data. It has already attracted widespread attention for various tasks such as node classification and link prediction. Existing research focuses more on graph convolutional neural networks (GCNs). However, it is usually overlooked that graph pooling can obtain graph representations by summarizing and down-sampling node information. Meanwhile, existing graph pooling methods mainly use top-k for node selection, but most of them consider only single view information when scoring nodes, and the k values in top-k are usually selected empirically. This work proposes the hierarchical multiview top-k pooling (HMTPool) with deep-Q-networks, which scores nodes taking into account multiview information (considering graph structure and features) and does not rely on the empirical adaptive selection of the best k value. HMTPool is a two-stage process. It first uses a variant GCN and multilayer perceptron to score the nodes from structural and feature perspectives, respectively and then performs fusion operations on the multiview information scores of the nodes. In addition, to select the optimal pooling ratio of top-k, we propose a deep-Q-network-based top-k (DTop-k) node selection method, which can adaptively select the best pooling ratio without prior knowledge. Experimental results on six TUDatasets and two Benchmarking GNNs datasets demonstrate the effectiveness of our proposed approach. © 2020 IEEE.

关键词： Convolution

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Time-Varying Functional Connectivity of Rat Brain during Bipedal Walking on Unexpected Terrain

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Cyborg and Bionic systems 2023年第1期4卷 392-405页

作者： Honghao Liu Bo Li Pengcheng Xi Yafei Liu Fenggang Li Yiran Lang Rongyu Tang Nan Ma Jiping He School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China School of Information and Communication Engineering North University of ChinaTaiyuan 038507China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China Department of Engineering Lancaster UniversityLancaster LA14YWUK

The cerebral cortex plays an important role in human and other animal adaptation to unpredictable terrain changes,but little was known about the functional network among the cortical areas during this *** address the question,we trained 6 rats with blocked vision to walk bipedally on a treadmill with a random uneven ***-brain electroencephalography signals were recorded by 32-channel implanted ***,we scan the signals from all rats using time windows and quantify the functional connectivity within each window using the phase-lag ***,machine learning algorithms were used to verify the possibility of dynamic network analysis in detecting the locomotion state of *** found that the functional connectivity level was higher in the preparation phase compared to the walking *** addition,the cortex pays more attention to the control of hind limbs with higher requirements for muscle *** level of functional connectivity was lower where the terrain ahead can be *** connectivity bursts after the rat accidentally made contact with uneven terrain,while in subsequent movement,it was significantly lower than normal *** addition,the classification results show that using the phase-lag index of multiple gait phases as a feature can effectively detect the locomotion states of rat during *** results highlight the role of the cortex in the adaptation of animals to unexpected terrain and may help advance motor control studies and the design of neuroprostheses.

关键词： Connectivity connectivity terrain

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Integrated Cam Contour Optimization Method Considering Kinematic and Dynamic Characteristics: A Paradigm of Offset Press Open-Close Gripper Mechanism

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Journal of Shanghai Jiaotong University (Science) 2024年 1-13页

作者： Li, Wenwei Cao, Shuai Qian, Qian Zhang, Yaling Chen, Nan Robotic Laboratory South China Robotics Innovation Research Institute Guangdong Foshan528300 China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Institute of Intelligent Manufacturing Guangdong Academy of Sciences Guangzhou510070 China Foshan Zhiyouren Technology Co. Ltd. Guangdong Foshan528300 China School of Mechanical Engineering Southeast University Nanjing211189 China

To efficiently search out the optimal cam contour, a software integrated optimization method considering cam mechanism’s kinematic and dynamic characteristics was presented, and its effectiveness was demonstrated by a case study of the cam contour optimization for an offset press open-close gripper mechanism. The acceleration curve and the residual vibration model of the follower were separately studied. A symmetric harmonic trapezoidal curve was designed to control the follower’s acceleration, and single-DOF lumped parameter torsional vibration model was proposed to describe the follower’s residual vibration. Accordingly, corresponding motion curve design software and Simulink vibration model of the follower were developed respectively, and they were integrated into an automatic optimization platform with iSIGHT. The multi-objective optimization with objectives of minimizing both the acceleration and the residual vibration of the follower was completed within the platform by using NSGA-II algorithm. An appropriate point with lower acceleration and residual vibration was chosen from Pareto front as an optimal solution of the follower’s motion curve. Based on the follower’s new motion curve, the actual cam contour was generated by inverse kinematic simulation in COSMOSMotion. The offset press that installed our new designed cam exhibited a lower vibration than the previous machine, and the maximum measured acceleration of the offset press at a printing speed of 15 000 r/h is reduced by 7.7%. © Shanghai Jiao Tong University 2024.

关键词： Acceleration

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An Efficient Hybrid Model Based on Modified Whale Optimization Algorithm and Multilayer Perceptron Neural Network for Medical Classification Problems

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Journal of Bionic Engineering 2022年第5期19卷 1504-1521页

作者： Saeid Raziani Sajad Ahmadian Seyed Mohammad Jafar Jalali Abdolah Chalechale Department of Computer Engineering Razi UniversityKermanshah ***Iran Faculty of Information Technology Kermanshah University of TechnologyKermanshah ***Iran Institute for Intelligent Systems Research and Innovation(IISRI) Deakin UniversityWaurn PondsMelbourne 3217Australia

Feedforward Neural Network(FNN)is one of the most popular neural network models that is utilized to solve a wide range of nonlinear and complex *** models such as stochastic gradient descent have been developed to train ***,they mainly suffer from falling into local optima leading to reduce the accuracy of ***,the convergence speed of training process depends on the initial values of weights and biases in ***,these values are randomly determined by most of the training *** deal with these issues,in this paper,we develop a novel evolutionary algorithm by modifying the original version of Whale Optimization Algorithm(WOA).To this end,a nonlinear function is introduced to improve the exploration and exploitation phases in the search process of ***,the modified WOA is applied to automatically obtain the initial values of weights and biases in FNN leading to reduce the probability of falling into local *** addition,the FNN model trained by the modified WOA is used to develop a classification approach for medical diagnosis *** medical diagnosis datasets are utilized to evaluate the efficiency of the proposed ***,four evaluation metrics including accuracy,AUC,specificity,and sensitivity are used in the experiments to compare the performance of classification *** experimental results demonstrate that the proposed method is better than other competing classification models due to achieving higher values of accuracy,AUC,specificity,and sensitivity metrics for the used datasets.

关键词： Feed forward neural network Meta-heuristic algorithm Whale optimization algorithm Optimization Classification Bionic algorithm

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User Perception and Evaluation of a Portrait Drawn by KUKA KR3 AGILUS Manipulator 9th

User Perception and Evaluation of a Portrait Drawn by KUKA K...

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9th International Conference on Interactive Collaborative robotics, ICR 2024

作者： Zagirov, Aidar Chebotareva, Elvira Osokin, Sergey Li, Hongbing Magid, Evgeni Intelligent Robotics Department Institute of Information Technology and Intelligent Systems Kazan Federal University 35 Kremlevskaya St. Kazan420008 Russia Department of Instrument Science and Engineering Shanghai Jiao Tong University Minhang Shanghai200240 China School of Electronic Engineering Tikhonov Moscow Institute of Electronics and Mathematics HSE University 34 Tallinskaya St. Moscow Russia

ISBN: (纸本)9783031713590

Creating an artistic portrait is considered one of the most complex areas of a generative art. Currently, generative artificial intelligence (AI) has made significant advancements in generating portraits of people based on photographic images. This has opened up new opportunities for utilizing AI achievements in robotic artistry. However, questions related to evaluation and human perception of such works, including their artistic value, remain open. In our work, we present experimental results of integrating the processing of human photographs using the generative model InstantID with a drawing robot and studying users’ reactions to the obtained images. In our experiments, we generated graphic portraits of people and constructed their images using KUKA KR3 AGILUS robot. We then asked participants to rate the resulting portraits based on three parameters: similarity/recognition, beauty/aesthetics, and evoked emotions. The results of the experiments can be used in social robotics, including art therapy that involves social robots and human-robot interaction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Social robots

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Learning Rat-Like Behavioral Interaction Using a Small-Scale Robotic Rat 12

Learning Rat-Like Behavioral Interaction Using a Small-Scale...

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12th International Conference on CYBER technology in Automation, Control, and intelligent systems, CYBER 2022

作者： Gao, Zihang Jia, Guanglu Xie, Hongzhao Guo, Xiaowen Fukuda, Toshio Shi, Qing Beijing Institute of Technology Ministry of Education Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Key Laboratory of Biomimetic Robots and Systems Beijing100081 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In the existing robot-rat interaction, robots usually exert influence as stimuli to observe the response of target rats. However, the above single-stimulation model from robot to rat lacks a two-way communication. Therefore, we proposed a method to learn the rat-like behavioral interaction. First, we constructed two behavior patterns in the interaction process between the two rats: the individual pattern and the interaction pattern. We divided the roles of the two rats into active stimulator and passive receiver. The stimulator executes the individual pattern, and the receiver switches between the two patterns. Which pattern the receiver executes depends on the probability of interaction. Secondly, we proposed a hypothesis concerning the behavioral interaction between two rats and controlled the interaction process between two robots. information entropy was used to measure the similarity between two robots and two rats. The results proved that the probability of interaction between rats depends on the distance of centroid and average relative velocity, and we obtained the optimal solution to express the relationship between them. In the future, the improvement of robots' interaction ability with rats will highly benefit from this study. © 2022 IEEE.

关键词： Rats

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FDNet: Remaining Useful Life Prediction for Lithium-Ion Batteries Based on Fourier Series and DenseNet 5

FDNet: Remaining Useful Life Prediction for Lithium-Ion Batt...

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5th International Conference on Machine Learning and Computer Application, ICMLCA 2024

作者： Chen, Siwen Zheng, Xiujuan Shanghai United Imaging Healthcare Co. Ltd. Shanghai China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Engineering Research Center for Metallurgical Automation and Measurement Technology Ministry of Education Wuhan China

ISBN: (纸本)9798331530334

To enhance the prediction accuracy of the remaining useful life (RUL) of lithium-ion batteries, this study proposes a novel RUL prediction model, termed FDNet, which integrates Discrete Fourier Series (DFS) and Densely Connected Convolutional Networks (DenseNet). In contrast to traditional methods that rely on one-dimensional (1D) numerical representations of time-series data, this model utilizes a two-dimensional (2D) visual representation for direct RUL prediction. First, the DFS is employed to convert 1D time-series signals into a 2D time-frequency domain, enabling the extraction of high-dimensional features from the original data. Then, these 2D images are subsequently input into DenseNet, which learns the mapping between the image features and the RUL targets. Finally, the proposed model is validated using the NASA lithium-ion battery aging dataset, and the results indicate that FDNet achieves superior prediction accuracy and exhibits notable robustness. © 2024 IEEE.

关键词： Prediction models

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UAV-Aided Multi-antenna Relay systems with Wireless Power Transfer for Maritime Communications 14th

UAV-Aided Multi-antenna Relay Systems with Wireless Power T...

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14th EAI International Conference on Wireless and Satellite systems, WiSATS 2024

作者： Li, Yuheng Zhou, Zhiquan Wang, Jinlong Wang, Lina Wang, Chenxu School of Information Science and Engineering Harbin Institute of Technology Weihai264209 China Shandong Provincial Key Laboratory of Marine Electronic Information and Intelligent Unmanned Systems Weihai264209 China Key Laboratory of Cross-Domain Synergy and Comprehensive Support for Unmanned Marine Systems Ministry of Industry and Information Technology Weihai264209 China

ISBN: (纸本)9783031862021

With the increase in maritime activities, traditional communication methods can no longer meet the needs of today’s maritime work, and the use of unmanned aerial vehicle(UAV) relay communications in marine scenarios has attracted more and more attention. In this paper, A long-distance three-node two-hop UAV relay system for maritime users is investigated. The UAV aerial relay node first transmits an energy-carrying radio frequency (RF) signal to the maritime user node, which then harvests energy and sends data information back to the UAV aerial relay node, which in turn forwards it to the land node. Considering the peculiarities of maritime communication channels, a novel land-air-maritime communication channel model is proposed. Utilizing Zero-Forcing/Zero-Transmission (ZFR/ZFT) technology, a precoding matrix for the aerial relay node is designed, followed by simulation and emulation, the performance of the channel is tested in the case of different transmission power of relay nodes or different number of antennas of relay nodes. © ICST institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2025.

关键词： Unmanned aerial vehicles (UAV)

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High-responsivity on-chip waveguide coupled germanium photodetector for 2 μm waveband

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Photonics Research 2024年第1期12卷 115-122页

作者： JIANING WANG XI WANG YIHANG LI YANFU YANG QINGHAI SONG KE XU Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of TechnologyShenzhen 518055China Department of Electronic&Information Engineering Harbin Institute of TechnologyShenzhen 518055China Department of Science Harbin Institute of TechnologyShenzhen 518055China

Recently,the emerging 2μm waveband has gained increasing interest due to its great potential for a wide scope of *** with the existing optical communication windows at shorter wavelengths,it also offers distinct advantages of lower nonlinear absorption,better fabrication tolerance,and larger free carrier plasma effects for silicon photonics,which has been a proven device *** much progress has been witnessed for silicon photonics at the 2μm waveband,the primary challenge still exists for on-chip *** the maturity and compatibility of the waveguide coupled photodetectors made of germanium,the 2μm regime is far beyond its cutoff *** this work,we demonstrate an efficient and high-speed on-chip waveguidecoupled germanium photodetector operating at the 2μm *** weak sub-bandgap absorption of epitaxial germanium is greatly enhanced by a lateral separation absorption charge multiplication *** detector is fabricated by the standard process offered by a commercial *** device has a benchmark performance with responsivity of 1.05 A/W and 3 dB bandwidth of 7.12 GHz,which is able to receive high-speed signals with up to 20 Gbit/s data *** availability of such an efficient and fast on-chip detector circumvents the barriers between silicon photonic integrated circuits and the potential applications at the 2μm waveband.

关键词： waveguide responsivity wave

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