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arXiv 2023年

作者： Ding, Yu Cong, Yirui Wang, Xiangke Cheng, Long College of Intelligence Science and Technology National University of Defense Technology Changsha410073 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

This article studies the distributed estimation problem of a multi-agent system with bounded absolute and relative range measurements. Parts of the agents are with high-accuracy absolute measurements, which are considered as anchors;the other agents utilize low-accuracy absolute and relative range measurements, each derives an uncertain range that contains its true state in a distributed manner. Different from previous studies, we design a distributed algorithm to handle the range measurements based on extended constrained zonotopes, which has low computational complexity and high precision. With our proposed algorithm, agents can derive their uncertain range sequentially along the chain topology, such that agents with low-accuracy sensors can benefit from the high-accuracy absolute measurements of anchors and improve the estimation performance. Simulation results corroborate the effectiveness of our proposed algorithm and verify our method can significantly improve the estimation accuracy. Copyright © 2023, The Authors. All rights reserved.

关键词： Multi agent systems

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The application and issuse of linear wireless sensor networks

The application and issuse of linear wireless sensor network...

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International Conference on system Science, Engineering Design and Manufacturing Informatization (ICSEM)

作者： Zhengjie Wang Xiaoguang Zhao Xu Qian School of Mechanical Electronic & Info. Engineering China University of Mining & Technology (Beijing) Beijing China College of Information and Electrical Engineering Shandong University of Science and Technology Qingdao China State Key Laboratory of Intelligent Control and Management of Complex Systems Chinese Academy of Sciences Beijing China

Wireless sensor networks consist of a large number of sensor nodes that have low power and limited transmission range and can be used in various scenario. The nodes can be deployed in the long and narrow region, such as road, bridge, tunnel and pipeline, to get some interesting information. The linear topology of these network application is different other application and have special feature, such as multi-hop, long delay, long distance and low reliability. This paper introduces the concept of linear wireless sensor networks and discusses the classification of topology and key issue of this network. The application of the linear wireless sensor network, such as road, bridge, tunnel and pipeline is presented. The research challenges are discussed at last in this paper.

关键词： Monitoring Reliability Collaboration Spread spectrum communication Hoses Topology Routing protocols

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A Negotiation-based Right-of-way Assignment Strategy to Ensure Traffic Safety and Efficiency in Lane Changes

arXiv

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arXiv 2019年

作者： Zhao, Can Li, Zhiheng Li, Li Wu, Xiangbin Wang, Fei-Yue Department of Automation Tsinghua University Beijing China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China Intel Labs China Intel Corporation Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

It is widely acknowledged that verifying the safety of autonomous driving strategies requires a substantial body of simulation testing and road testing. In recent years, the formal safety methods represented by Responsibility-Sensitive Safety (RSS) have encouraged low-cost autonomous driving safety research, benefitting from its accurate assessment of safety and clear division of responsibilities. However, how to maintain traffic efficiency while ensuring safety remains a challenge. To address this problem, this paper proposes a formulized negotiation-based lane-changing strategy that makes a trade-off between safety and efficiency. Both theoretical analysis and numerical experimental results shows that compared to RSS, our strategy can noticeably improve the success rate of changing lanes on the premise of safety. Copyright © 2019, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Pruning-Based YOLOv4 Algorithm for Underwater Gabage Detection

Pruning-Based YOLOv4 Algorithm for Underwater Gabage Detecti...

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第40届中国控制会议

作者： Manjun Tian Xiali Li Shihan Kong Licheng wu Junzhi Yu School of Information Engineering Minzu University of China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Dept.Adv.Manuf.Robot. BIC-ESAT College of Engineering Peking University

To tackle the problem of aquatic environment pollution, a vision-based autonomous underwater garbage cleaning robot has been developed in our laboratory. This paper proposes a garbage detection method based on a modified YOLOv4,allowing high-speed and high-precision object detection. More specifically, the YOLOv4 algorithm is chosen as a basic neural network framework to perform object detection. With the purpose of further improvement on the detection speed, the channel pruning and layer pruning are implemented on the trained YOLOv4 model, while the fine-tuned mechanism assists the pruned model to restore accuracy. In virtue of the improved detection methods, the robot has the ability to collect garbage *** experimental results indicate that the pruned YOLOv4 detection method can still maintain the high performance even though the parameter amount is 7.062% of the original model.

关键词： Object detection aquatic environment garbage cleaning robot modified YOLOv4

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2013年 7888 LNAI卷 vi页

作者： Liu, Derong Alippi, Cesare Zhao, Dongbin Hussain, Amir Chinese Academy of Sciences Institute of Automation State Key Laboratory of Management and Control for Complex Systems Beijing 100190 China Politecnico di Milano Dipartimento di Elettronica Informazione e Bioingegneria 20133 Milano Italy University of Stirling Department of Computing Science and Mathematics Stirling FK9 4LA United Kingdom

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Urban trip generation forecasting based on gradient boosting algorithm 1

Urban trip generation forecasting based on gradient boosting...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Li, Zhishuai Xiong, Gang Zhang, Yu Zheng, Meng Dong, Xisong Lv, Yisheng Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Municipal Institute of City Planning and Design Traffic Planning Department Beijing China

ISBN: (纸本)9781665433372

The four-step transportation model plays an important role in urban planning. The quality of the first phase, i.e. trip generation, determines the performance of the global course. The majority of trip generation forecasting models highly rely on mathematical derivation and have many predictor variables during the prediction, which leads to low accuracy of results and requires laboriously hand-crafted design of input vectors. This paper is the first to introduce the gradient boosting decision tree (GBDT) algorithm for trip generation prediction, and harmonizes such a powerful machine learning method with traditional urban planning requirements to achieve better prediction performance. Unlike the commonly used linear regression method, GBDT can automatically perform feature selection and model the non-linear relationships between input and output variables. Experimental results on real-world residential travel census in Beijing prove that the GBDT model significantly outperforms the baseline and can forecast the trip generation more accurately. © 2021 IEEE.

关键词： Decision trees

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Geometry Problem Solving Based on Counter-Factual Evolutionary Reasoning 19

Geometry Problem Solving Based on Counter-Factual Evolutiona...

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19th IEEE International Conference on Automation Science and Engineering, CASE 2023

作者： Song, Bing Xiong, Gang Shen, Zhen Zhu, Fenghua Lv, Yisheng Ye, Peijun Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Institute of Automation Chinese Academy of Sciences The Beijing Engineering Research Center of Intelligent Systems and Technology China Chinese Academy of Sciences The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Dongguan523808 China Qingdao Academy of Intelligent Industries Intelligent Manufacturing Center Qingdao266000 China

ISBN: (纸本)9798350320695

As a representative topic in natural language processing and automated theorem proving, geometry problem solving requires an abstract problem understanding and symbolic reasoning. A major challenge here is to find a feasible reasoning sequence that is consistent with given axioms and the theorems already proved. Most recent methods have exploited neural network-based techniques to automatically discover eligible solving steps. Such a kind of methods, however, is greatly impacted by the expert solutions for training. To improve the accuracy, this paper proposes a new method called counterfactual evolutionary reasoning, which uses a generative adversarial network to generate initial reasoning sequences and then introduces counterfactual reasoning to explore potential solutions. By directly exploring theorem candidates rather than the neural network selection, the new method can sufficiently extend the searching space to get a more appropriate reasoning step. Through comparative experiments on the recent proposed Geometry3k, the largest geometry problem solving dataset, our method generally achieves a higher accuracy than most previous methods, bringing an overall improvement about 4.4% compared with the transformer models. © 2023 IEEE.

关键词： Geometry

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A Two-layer Adaptive control Strategy for Photovoltaic Power in Different Scenarios

A Two-layer Adaptive Control Strategy for Photovoltaic Power...

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Energy Engineering and Power systems (EEPS), International Conference on

作者： Yanghui Wan Jiahao Yan Tianfeng Chu Yaping Li Kun Yuan Kaifeng Zhang Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Southeast University Nanjing China Power Automation Department China Electric Power Research Institute(Nanjing) Nanjing China Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. Shenyang China

Currently, control strategies for distributed photovoltaic (PV) power generation are relatively single and rigid, and cannot flexibly adapt to the diverse demands of power grids in different scenarios. Firstly, this paper analyzes the adaptive relationship between different dispatching demands, the regulation ability of distributed PV, and the characteristics of the local voltage. Secondly, for different scenarios, the coordinated controller determines the reference values of active power and reactive power given to the inverter. Thus, distributed PV power control modes which can adapt to different scenarios have been established. Then, these control modes can be classified into single control modes and compound control modes according to the complexity of scenario demands. On this basis, a specific two-layer adaptive control strategy and process of distributed PV power generation in a low-voltage distribution network are further proposed, which takes into account both external demands of the distribution network and the regulation ability of distributed PV. Finally, a case study is given to verify the rationality and effectiveness of the two-layer adaptive scenarios control strategy. This strategy can effectively improve the comprehensive support ability of distributed PV power generation towards the power grid in multiple scenarios, and improve the stable operation level of the regional power grid.

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Unimodular Complete Complementary Sequence with Optimal Trade-off between Auto- and Cross-ambiguity Functions for MIMO Radars

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Li, Yuke Zhou, Yongxing Li, Xueru Wang, Junbo Wang, Yutong Fan, Lili Wang, Fei-Yue Waytous Co. Ltd. Beijing China Consumer BG Huawei Technologies Co. Ltd Beijing China School of Software Northwestern Polytechnical University Xi'an China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China School of Information and Electronics Beijing Institute of Technology Beijing China

It is difficult to design unimodular sequences with both good auto-ambiguity functions (AF) and cross-ambiguity functions (CAF), due to its nonconvex and higher cardinality property. To address this problem, we propose a Pareto optimization framework to reach an optimal tradeoff between AF and CAF. Besides, we also propose a novel convolution-based multi-objective optimization algorithm to optimize the conventional metrics including peak sidelobe level (PSL) and integrated sidelobe level (ISL). In this way, the generated sequences are Doppler resilient with the desired shape of aperiodic or periodic AFs. Compared with the state-of-the-art methods, simulation experimental results indicate the PSL metric of AF and CAF can be both suppressed to -72dB under the same system parameters, obtaining a minimum of 7 dB gain. IEEE

关键词： Multiobjective optimization

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A Novel Person Re-ID Method based on Multi-Scale Feature Fusion

A Novel Person Re-ID Method based on Multi-Scale Feature Fus...

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Chinese control Conference (CCC)

作者： Yuanyuan Li Xiaofei Wang Zhiqin Zhu Xinghua Huang Penghua Li Guanqiu Qi Yujun Rong Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Complex System Safety and Control Ministry of Education Chongqing University Chongqing China Computer Information Systems Department Buffalo State College Buffalo NY USA China Mobile (Hangzhou) Information Technology Co. Ltd. Hangzhou China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

Person re-identification (Re-ID) is a challenging but significant research topic. Previous methods based on global features are not pay much attention to the fine-grained feature information. While the methods based on local features strictly rely on the accurate pedestrian detection bounding-boxes to align the image pairs. In this paper, the Multi-Scale Feature Fusion Network is proposed which can extract global and local features simultaneously and to learn jointly. The network structure consists of two branches. One is a global branch for global feature learning, in this branch, we extract the whole body feature information of human body to express the pedestrian image as a whole. The other is a local branch for local feature learning. In the local branch, according to the characteristics of pedestrian's human structure, we segment the image into 6 horizontal strips to bring the local feature representation of the pedestrian image. In addition, we use a novel integration of multiple loss functions to further improve the recognition accuracy of the network. Experiments on Market-1501 and DukeMTMC-reID datasets show that our proposed method can achieve state-of-the-art results.

关键词： Feature extraction Task analysis Training Measurement Smoothing methods Electronic mail Machine learning

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