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第34届中国控制与决策会议

作者： Ziyao Wang Yiye Wang Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

Natural Locomotion interface(NLI) is critical to expanding the users' exploration of scenes in virtual reality and improving user *** on the 2D motion platform,users can achieve a natural locomotion experience in a limited physical *** a small-scale 2D motion platform,an ideal situation is that the velocity of the platform can always be synchronized with the user's actual intended velocity,so that the user's center of mass is kept at the center of the *** puts a brand new requirement on the performance of the platform *** paper designs an acceleration-level state feedback controller for the small-scale 2D motion *** the user's intended acceleration as an external disturbance,it is estimated by introducing a disturbance state observer;for the user' s velocity on the platform,a linear state observer is used to estimate it;then takes the estimated values as feedforward terms to compensate the *** with the HCMK1 2D motion platform,we implemented the controller and verified it to be *** recording the data of the user walking along the circle and the square trajectory,it was verified that the designed controller has good control performance for the user's motion and the state observers a great performance to quickly track the user's intended acceleration and the user's velocity on the platform.

关键词： Virtual Reality Nature Locomotion Interface State Observer 2D-Motion Platform

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Automatic Reading System of Pointer Meters in Gas Gathering Stations

Automatic Reading System of Pointer Meters in Gas Gathering ...

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第34届中国控制与决策会议

作者： Yaqing Chang Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

In gas gathering stations,pointer meters are usually read by workers,which takes high labor costs and has low *** solve these problems and build intelligent gas gathering stations,this paper proposes an automatic reading system for real-time and accurate pointer meter reading.A new dataset is first constructed,which consists of700 pointer meter images with different angles,illumination and *** on the dataset,the deep learning model YOLOv5 is trained for dial and pointer *** the pointer mask output by YOLOv5,image preproces sing is used to separate the pointer from the background and generate the pure *** improved skeleton extraction algorithm and the Hough line detection algorithm are combined to extract the pointer center *** the dial image output by YOLOv5,feature matching and perspective transformation are adopted for position ***,pointer reading is obtained by applying the angle method to the corrected dial and the pointer center *** experiments demonstrate the high accuracy and efficiency of the proposed *** strong robustness to various interference factors in complex environments are also validated.

关键词： Pointer Meter Automatic Reading YOLOv5 Object Detection Skeleton Extraction

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An Effective Hybrid Genetic Algorithm for the Multi-Robot Task Allocation Problem with Limited Span

SSRN

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SSRN 2024年

作者： Liu, Wenbo Kuang, Zhian Zhang, Yongcong Zhou, Bo He, Pengfei Li, Shihua School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Shanghai Friendess Electronic Technology Shanghai201100 China

Multi-robot task allocation is one of the most interesting multi-robot systems that have gained considerable attention due to various real-world applications. In this paper, we focus on a multi-robot task allocation problem where a set of industrial robots, which are installed on a gantry and have a limited working span, have to jointly perform a set of weld lines in large size. We present a mathematical model that captures the objective of minimizing the cycle time, i.e., the time required to complete a given set of weld lines. Due to the inherent difficulty of the problem, we propose an effective hybrid genetic algorithm to solve it. Because the robots are associated with a limited working span, the algorithm integrates a specific region division algorithm to divide the workpieces into a set of regions where the robots can reach all the weld lines in each region. It also incorporates a dedicated route-based crossover to generate promising offspring solutions and an effective neighborhoodbased local search procedure to improve each offspring solution as much as possible. Extensive experimental results on three benchmark instances show that the algorithm significantly outperforms reference methods. Additional experiments on real-world instances are presented to verify the algorithm’s effectiveness in solving the multi-robot task allocation problem with limited span. © 2024, The Authors. All rights reserved.

关键词： Industrial robots

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Hotspot detection of photovoltaic modules in infrared thermal image based on saliency analysis

Hotspot detection of photovoltaic modules in infrared therma...

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第34届中国控制与决策会议

作者： Yiye Wang Yu Shen Chenxi Li Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

With the increasing awareness of environmental protection,the solar photovoltaic(PV) industry has been developing dramatically in recent *** module is an important part of PV power generation *** all the defect types of PV modules,hotspots occur more frequently and cause more serious ***,it is necessary to detect *** approach is proposed using saliency analysis method for hotspot detection,combing the cognitive property about visual saliency and the temperature property of *** only does this approach not require manual threshold setting,but also it does not require a large number of learning *** approach can also achieve the defect diagnosis and hotspot location when compared with the electrical characterization *** infrared thermal(IRT)images trained in experiments are obtained using the thermographic camera FLIR Vue Pro with the unmanned aerial vehicle from a PV plant in Jiangsu,*** 135 IRT images are collected and 1020 PV modules are extracted from these *** have proved great accuracy and robustness when using the proposed method to detect hotspots.

关键词： Hotspot PV module IRT image Saliency analysis Graph

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Design of redundant control system for Antarctic unattended energy platform based on RS-485

Design of redundant control system for Antarctic unattended ...

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第34届中国控制与决策会议

作者： Chenwei Sun Kanjian Zhang Haikun Wei Jian Ge Shixiong Fang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

The successful operation of the Antarctic unattended energy platform with data storage and other functions can provide electric energy for other scientific research ***,its performance needs further improvement due to the lack of experience and the special environmental constraints of *** on the above reasons,this paper proposes an optimized design of unattended energy control platform from the perspective of improving the reliability and safety of the *** to the actual project requirements,the engine control system of the unattended energy platform is designed and *** control system part is designed as a control mode with RS-485 control combined with hardware interface features to realize the direct communication between the upper computer and the generator set and the related hardware control *** redundant control is added to effectively avoid the loss of connection of key equipment of the whole device due to irreparable failure of PLC in the previous system,which improves the reliability of the platform system.

关键词： RS-485 communication Redundant control system Data acquisition and Reliability

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Joint Beam Management and SLAM for mmWave Communication systems

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IEEE Transactions on Communications 2023年第10期71卷 6162-6179页

作者： Que, Hang Yang, Jie Wen, Chao-Kai Xia, Shuqiang Li, Xiao Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Zte Corporation Shenzhen518055 China State Key Laboratory of Mobile Network and Mobile Multimedia Shenzhen518055 China Southeast University National Mobile Communications Research Laboratory Frontiers Science Center for Mobile Information Communication and Security Nanjing210096 China

The millimeter-wave (mmWave) communication technology, which employs large-scale antenna arrays, enables inherent sensing capabilities. Simultaneous localization and mapping (SLAM) can utilize channel multipath angle estimates to realize integrated sensing and communication design in 6G communication systems. However, existing works have ignored the significant overhead required by the mmWave beam management when implementing SLAM with angle estimates. This study proposes a joint beam management and SLAM design that utilizes the strong coupling between the radio map and channel multipath for simultaneous beam management, localization, and mapping. In this approach, we first propose a hierarchical sweeping and sensing service design. The path angles are estimated in the hierarchical sweeping, enabling angle-based SLAM with the aid of an inertial measurement unit (IMU) to realize sensing service. Then, feature-aided tracking is proposed that utilizes prior angle information generated from the radio map and IMU. Finally, a switching module is introduced to enable flexible switching between hierarchical sweeping and feature-aided tracking. Simulations show that the proposed joint design can achieve sub-meter level localization and mapping accuracy (with an error © 1972-2012 IEEE.

关键词： Mapping

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Inverse Reinforcement Learning Integrated Reinforcement Learning for Single Intersection Traffic Signal control

Inverse Reinforcement Learning Integrated Reinforcement Lear...

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International Conference on Industrial Artificial Intelligence (IAI)

作者： Shiyi Gu Tingting Zhang Ya Zhang School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China College of Command and Control Engineering Army Engineering University Nanjing China

Traffic Signal control (TSC) optimization is vital for efficient traffic flow in urban intersections. Recent research has explored the application of Reinforcement Learning (RL) agents to tackle TSC challenges. However, the selection of an appropriate reward function in RL agent training still relies on subjective judgment and experience. To address this issue, an Inverse Reinforcement Learning (IRL) integrated RL algorithm is proposed. In the IRL learning section, expert trajectory data are collected and analyzed by Relative Entropy IRL (REIRL). The latent reward of expert policy is reconstructed and utilized in RL agent training process. In the RL control section, a Double Dueling Deep Q Network is applied under a cycle control framework. As verified in simulations, the introduction of expert experience improves the performance of the RL agent to the expert level and concurrently enables robustness to expert policy noises.

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Physics-Guided Human Motion Capture with Pose Probability Modeling

arXiv

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arXiv 2023年

作者： Ju, Jingyi Huang, Buzhen Zhu, Chen Li, Zhihao Wang, Yangang Southeast University China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Huawei Noah's Ark Lab Canada

Incorporating physics in human motion capture to avoid artifacts like floating, foot sliding, and ground penetration is a promising direction. Existing solutions always adopt kinematic results as reference motions, and the physics is treated as a postprocessing module. However, due to the depth ambiguity, monocular motion capture inevitably suffers from noises, and the noisy reference often leads to failure for physics-based tracking. To address the obstacles, our key-idea is to employ physics as denoising guidance in the reverse diffusion process to reconstruct physically plausible human motion from a modeled pose probability distribution. Specifically, we first train a latent gaussian model that encodes the uncertainty of 2D-to-3D lifting to facilitate reverse diffusion. Then, a physics module is constructed to track the motion sampled from the distribution. The discrepancies between the tracked motion and image observation are used to provide explicit guidance for the reverse diffusion model to refine the motion. With several iterations, the physics-based tracking and kinematic denoising promote each other to generate a physically plausible human motion. Experimental results show that our method outperforms previous physics-based methods in both joint accuracy and success rate. More information can be found at https://***/Me-Ditto/Physics-Guided-Mocap. Copyright © 2023, The Authors. All rights reserved.

关键词： Kinematics

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Data-Driven Distributed Robust Consensus Kalman Filtering for Sensor Networks

Data-Driven Distributed Robust Consensus Kalman Filtering fo...

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2021 China Automation Congress, CAC 2021

作者： Zhou, Ziai Wu, Hao Zhang, Ya School of Automation Southeast University Nanjing China 210096 Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China 210096

ISBN: (纸本)9781665426473

This paper mainly studies the distributed robust filtering problem for wireless sensor networks without knowing the variance of the driving noise and measuring noise. A distributed filtering algorithm based on leader-follower consensus strategy is developed. Firstly, from limited sampling data of noises, the empirical distribution of the noises which play a critical role in filtering is given. Secondly, by formulating the problem as a zero-sum game problem and using dynamic programming approach, an optimal distributed robust filtering policy with Wasserstein penalty for the leader is obtained. Then, by using an adaptively weighting average consensus protocol, the filtering algorithm for followers is given. The effectiveness of the proposed filter is demonstrated through simulations. © 2021 IEEE

关键词： Dynamic programming

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Variable impedance control method for robot contact force based on TD3 algorithm

Variable impedance control method for robot contact force ba...

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2022 Chinese Automation Congress, CAC 2022

作者： Shen, Xin Ma, Kaiwei Yang, Mingxing Gao, Shuang Chao, Shuo Xu, Fengyu College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications Nanjing210023 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Anhui Province Key Laboratory of Special Heavy Load Robot Maanshan243032 China

ISBN: (纸本)9781665465335

As a common method of traditional force control, impedance control has been widely used in robot machining field. However, impedance control with fixed parameters cannot dynamically adapt to the manufacturing environment. This paper presents a variable impedance control method for contact forces based on the TD3 (Twin Delayed Deep Deterministic Policy Gradient) algorithm. The method builds on the original impedance model to obtain the optimal impedance parameters for each stage by stochastic exploration of the continuous action space, reducing the reliance on human experience and multiple attempts in the selection of traditional impedance parameters. In this paper, gantry robot is taken as the research object. The simulation results show that the variable impedance control method has faster adjustment time and more stable, and the average position tracking error is about 0.11cm and the force tracking error is about 0.01N. © 2022 IEEE.

关键词： Force control

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