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36th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2021

作者： Qiu, Houhan Lin, Zhicheng Li, Jun Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781665437127

Semantic SLAM can achieve the acquisition of environmental semantic information and increase the understanding of the environmental content. Therefore, it has received extensive attention from academia and industry. In the most existing work, the visual SLAM and deep learning algorithms are combined, and the point cloud fusion method is used to build maps. It is difficult to be directly applied to robot navigation due to problems of time misalignment of sensor data, mismatched detection ranges, and inconsistent accuracy. In this paper, a method of building a semantic map is proposed by combining lidar, camera, odometer. First, the semantic information and position information of the target object are obtained by the YOLO v3 algorithm through the camera, and the grid map is constructed by using the Gmapping algorithm. Second, the semantic information and position information are merged into the grid semantic map to form a semantic grid map. Finally, the effectiveness and feasibility of this method are verified by these experiments. © 2021 IEEE.

关键词： Cameras

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A Pursuit Strategy for Multi-Agent Pursuit-Evasion Game via Multi-Agent Deep Deterministic Policy Gradient Algorithm

A Pursuit Strategy for Multi-Agent Pursuit-Evasion Game via ...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Ye, Jianfeng Wang, Qing Ma, Bei Wu, Yongbao Xue, Lei School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China SEU-Monash Joint Graduate School Southeast University Nanjing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

This paper studies a classical pursuit-evasion problem. The pursuer attempts to capture the faster evader in a bounded area. The velocity of evader is 1.2 times as fast as the pursuers'. All of them have adaptive strategies. We use game theory to model the multi-agent pursuit-evasion game and prove that the game model has Nash equilibrium. Then, we modify the multi-agent deep deterministic policy gradient (MADDPG) algorithm for seeking the Nash equilibrium. The simulation examples are given to illustrate the effectiveness of the designed method. © 2022 IEEE.

关键词： Game theory

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Estimation of Metro Passenger Capacity Based on Passenger-Train Matching Model 3rd

Estimation of Metro Passenger Capacity Based on Passenger-Tr...

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3rd International Conference on Information control, Electrical engineering, and Rail Transit, ICEERT 2023

作者： Mei, Zhenkun Chen, Beijia Liu, Jiajun Shao, Jiayu Zhang, Ning Suzhou Rail Transit Group Co. Ltd. Jiangsu Suzhou215004 China School of Automation Southeast University Jiangsu Nanjing210096 China Key Laboratory of Measurement and Control of Complex Engineering Systems Ministry of Education Southeast University Jiangsu Nanjing210096 China ITS Engineering Research Center Ministry of Education Southeast University Jiangsu Nanjing211189 China

ISBN: (纸本)9789819788903

In the present scenario of the ‘one-tapin-one-tapout’ operation mode in urban rail transportation, determining passenger travel trajectories is challenging, thereby decreasing the effective counting of passengers on trains. In order to address this issue, a method for calculating passenger capacity on trains was developed by analyzing passenger travel information extracted from AFC data and train timetables. First, this research estimated the components of journey time to infer and reconstruct the passenger's specific spatiotemporal travel trajectory. The passenger-train matching model was then used to assign passengers to specific trains and calculate the passenger load of different trains at each station. At last, it took Suzhou Metro Line 3 as an example and analyzed the spatiotemporal distribution of urban rail transit passenger flow on a single line based on the proposed passenger-train model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Urban transportation

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Robust control Analysis With Model Transformation for Interval Type-2 Fuzzy systems

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IEEE Transactions on Fuzzy systems 2025年

作者： Yang, Jie Gai, Shaoyan Da, Feipeng Xie, Wenbo Southeast University School of Automation Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing210096 China Shanghai University and Shanghai Artificial Intelligence Laboratory School of Mechatronic Engineering and Automation Shanghai200444 China

To address the problem of robust stability analysis for interval type-2 fuzzy systems (IT2FSs), this paper proposes an innovative analysis approach based on model transformation. Firstly, a classical piecewise linear approximation method is utilized to process the upper boundary membership functions (UMFs) and lower boundary membership functions (LMFs) of the footprint of uncertainty (FOU) in IT2FSs, resulting in linear boundary membership functions (MFs) that are more convenient for analysis, along with the corresponding approximation error functions. Subsequently, a novel error model transformation method is introduced to handle these error terms. By constructing new fuzzy rules and MFs, the boundary error terms are converted into a new fuzzy model, thereby incorporating more information about the error functions into the stability analysis. Based on this model, a robust stability condition in the form of linear matrix inequalities (LMIs) are derived, achieving improved robustness. Finally, the effectiveness of the proposed method is validated through simulations on real-world systems, and its superiority is demonstrated by comparison with existing methods. © 2025 IEEE.

关键词： Membership functions

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Hazard-Aware Weighted Advantage Combination for UAV Target Tracking and Obstacle Avoidance

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IEEE/CAA Journal of Automatica Sinica 2024年第6期12卷 1260-1271页

作者： Xu, Lele Liu, Jian Chang, Xiaoguang Liu, Xuping Sun, Changyin The School of Artificial Intelligence Anhui University Hefei230601 China The School of Automation the Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

In recent years, the rapid evolution of unmanned aerial vehicles (UAVs) has brought about transformative changes across various industries. However, addressing fundamental challenges in UAV technology, particularly target tracking and obstacle avoidance, remains crucial for wildlife protection, military industry security, etc. Many existing methods based on reinforcement learning to solve UAV multi-tasks need to be redesigned and retrained, and cannot be quickly and effectively extended to other scenarios. To this end, we propose a novel solution based on a hazard-aware weighted advantage combination for UAV target tracking and obstacle avoidance. First, we independently trained the UAV target tracking and obstacle avoidance using the Dueling Double Deep Q-Network reinforcement learning algorithm. Subsequently, in a multitasking scenario, we introduce the two pre-trained networks. Meanwhile, we design a weight determined by the present risk level encountered by the UAV. This weight is utilized to perform a weighted summation of the advantage values from both networks, eliminating the need for retraining to obtain the final action. We validate our approach through extensive simulation experiments in the robotics simulator known as CoppeliaSim. The results demonstrate that our method outperforms current state-of-the-art techniques, achieving superior performance in both tracking accuracy and avoidance of collisions. © 2013 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Bayesian Framework for Multi-User Cooperative Radio SLAM 35

Bayesian Framework for Multi-User Cooperative Radio SLAM

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Que, Hang Yang, Jie Du, Tao Xia, Shuqiang Wen, Chao-Kai Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing211189 China Southeast University Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Zte Corporation Shenzhen518001 China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518001 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung804 Taiwan

ISBN: (纸本)9798350362244

The advancement of millimeter-wave communication technology heralds new sensing capabilities. By leveraging channel multipath parameter estimates, we can harness simultaneous localization and mapping (SLAM) for precise user equipment (UE) localization and radio map construction in 6 G communication systems. Particularly in multi-UE scenarios, SLAM empowers base stations to amalgamate the local radio maps of various UEs efficiently. This study introduces a novel Bayesian framework specifically designed for multi-UE SLAM, complemented by a tailored factor graph. We also unveil a two-stage multi-UE SLAM algorithm. Our simulation results reveal that this algorithm substantially enhances radio map construction accuracy by 4 8. 5 % and UE localization accuracy by 13.5 %, outperforming single-UE cases. Moreover, the algorithm demonstrates remarkable adaptability to environmental changes, showcasing its potential for long-term evolution in dynamic settings. © 2024 IEEE.

关键词： Long Term Evolution (LTE)

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Task Sequence Planning Algorithm for Cooperative Assembly of Dual-arm Robot

Task Sequence Planning Algorithm for Cooperative Assembly of...

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2021 China Automation Congress, CAC 2021

作者： Zhang, Jin Gan, Yahui Wang, Zhengwei Dai, Xianzhong School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781665426473

Dual-arm collaborative robots have gradually become a research hotspot in the field of robotics due to their unique collaboration and flexibility, and they have a wide range of application prospects especially in the assembly manufacturing industry. However, the existing dual-arm robot lacks autonomy in assembly operations, especially when faced with a large number of randomly placed assembly parts, how to make the robot have independent assembly task decision-making ability is a challenge. In response to this problem, this paper proposes a new dual-arm robot collaborative assembly task sequence planning algorithm, which fully considers the constraints of the dual-arm robot's mechanical structure, kinematics, characteristics of objects to be assembled, interference between objects, etc.. Firstly, The algorithm uses the Monte Carlo method to analyze the working space of the left and right arms of the dual-arm robot, while taking into account the structural constraints of the robot. Then, according to the characteristics of the object to be assembled, the idea of interference sphere is proposed to analyze the interference between objects in the assembly task. The influence of the operation, and finally combined with the movement cost of the dual-arm assembly, the assembly task sequence is effectively planned. The algorithm was verified by simulation using the ABB YuMi dual-arm collaborative robot, and the experimental results proved the feasibility and effectiveness of the algorithm. © 2021 IEEE

关键词： Monte Carlo methods

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Effective Indoor Fire Detection with Channel Shuffle Module 21

Effective Indoor Fire Detection with Channel Shuffle Module

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5th International Conference on Computer Science and Application engineering, CSAE 2021

作者： Ge, Haotian Cao, Yichao Lu, Xiaobo School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781450389853

In recent years, methods based on computer vision and deep learning become the mainstream approaches in fire detection. However, the expensive computation cost of 3D convolutional neutral network (CNN) is unbearable and it is difficult for them to capture the fire regions of videos in time. In this paper, we design a module named channel shuffle module (CSM) based on 2D CNN to keep the balance between computation cost and accuracy. By fusing RGB frame and differential frame, CSM improves the ability of 2D CNN in temporal information extraction which much less cost than methods based on 3D CNN. Four different structures of CSM are proposed and we choose the best one by experiment results. Also, experiments prove that the performances of TSN and TSM are improved with CSM in sequence classification. The accuracy of TSM with CSM is 99.2045%, false positive rate reaches 0.7890% and false negative rate reaches 0.4530%, which demonstrates the efficiency of CSM in temporal feature modeling.. © 2021 Association for Computing Machinery. All rights reserved.

关键词： Fires

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A Two-step Model for Multi-object Tracking 21

A Two-step Model for Multi-object Tracking

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5th International Conference on Computer Science and Application engineering, CSAE 2021

作者： Zhang, Shuaishuai Lu, Xiaobo Du, Songlin Southeast University Key Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of Education School of Automation Nanjing China

ISBN: (纸本)9781450389853

Multi-object tracking is widely used in video analysis. However, due to the limitation of detector performance, many multi-object tracking models have the problem of detecting two objects into one object in some occlusion scenes. In this paper, we propose a twostep model for handling this problem. In the first step model, the non-occlusion targets are detected and embeddings are extracted, while the occlusion areas are identified. The second step model processes the occlusion areas to obtain occlusion targets' accurate positions and embeddings. Finally, we integrate and optimize the output results of the two steps models. Experiments show that the number of false positives and missed positives in our model's object detection is significantly reduced. The multi-object tracking performance (MOTA metric) is improved by nearly 3% compared with other models.. © 2021 Association for Computing Machinery. All rights reserved.

关键词： Embeddings

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Research on Drag control Algorithm of Cooperative Robot Based on Torque Compensation

Research on Drag Control Algorithm of Cooperative Robot Base...

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2021 China Automation Congress, CAC 2021

作者： Zhu, Dezhi Gan, Yahui Dai, Xianzhong School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781665426473

At present, the teaching methods of collaborative robot drag based on joint current feedback mainly include integral and partial dynamics model, both of which can make robots dragged. However, there are few researches aimed at the advantages and disadvantages of the drag effect and the specific application requirements of the systematic comparative study. Based on the above problems, two zero-force control methods are used on the same 6 degree-of-freedom(DOF) cooperative robot in this paper. And method of torque compensation is improved by parameter identification. Firstly, both of the two methods need to model and analyse the robotic arm. However, processes of the method based on integral dynamics model are modeling, excitation trajectory, filtering, identification and vertification. The zero-force control based on partial dynamics model mainly focuses on the compensation of gravity torque and static friction torque. The gravity term in the dynamic equation is adopted by modeling. The difference in this part is that the parameters of gravity moment function are identified, that is, the weight moment is calculated under the condition of the mass and center of mass deviation are unknown. Finally, NaiWei robot which is a six-joints cooperative robot in China is taken as the experimental object to test and compare. The experimental results show that method of partial dynamics model needs smaller force than integral dynamics model. And the comparison of drag power can be displayed by sensor. © 2021 IEEE

关键词： Force control

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