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13th IEEE International Conference on CYBER Technology in automation, control, and Intelligent Systems, CYBER 2023

作者： Zeng, Sheng Sun, Xiao Chen, Kang Huang, Weibing Chen, Yi Chen, Dan Xu, Zhezhuang College of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou University Education Department of Fujian Province Fuzhou350000 China Evomotion Co. Ltd. Guangdong Shenzhen518000 China

ISBN: (纸本)9798350315196

High cost of environmental interaction and low data efficiency limit the development of reinforcement learning in robotic grasping. This paper proposes an end-to-end robotic grasping method based on offline reinforcement learning via sequence modeling. It considers the most recent n-step history to assist the agent in making decisions, where a predictive model learns to directly predict actions from raw image inputs. The experimental results show that our method can achieve higher grasping success rate with less training data than traditional reinforcement learning algorithms in offline setting. © 2023 IEEE.

关键词： Reinforcement learning

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Non-cooperative Game-Oriented Optimal Prescribed Performance control for Underactuated Mechanical Systems with Asymmetric Constraints

Non-cooperative Game-Oriented Optimal Prescribed Performance...

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2024 China automation Congress, CAC 2024

作者： Liu, Lian Wei, Cui Chen, Ye-Hwa Zhang, Dengfeng Wei, Yanling College of Electrical Engineering and Control Science Nanjing Tech University Nanjing China Institute of Intelligent Manufacturing Nanjing Tech University Nanjing China George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta United States School of Automation Southeast University Nanjing China

ISBN: (纸本)9798350368604

This paper explores the application of non-cooperative game theory in achieving optimal prescribed performance control for uncertain underactuated mechanical systems. The study addresses scenarios characterized by time-varying (potentially rapid) and bounded uncertainties. Utilizing a constraint-following control design approach, we apply the prescribed transient and steady-state performance (TSSP) criteria to the constraint-following error. Additionally, we employ state transformation techniques to implement the prescribed performance control. We introduce a prescribed performance control methodology with two adjustable parameters and demonstrate the process of determining the optimal design for these parameters through Nash games. Our findings indicate a significant enhancement in the overall system performance, thus confirming the efficacy of the optimization method grounded in non-cooperative game theory. © 2024 IEEE.

关键词： Optimal control systems

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Predicting the State of Crane Spreader for Steel Bar Delivery Based on Machine Learning 13

Predicting the State of Crane Spreader for Steel Bar Deliver...

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13th IEEE International Conference on CYBER Technology in automation, control, and Intelligent Systems, CYBER 2023

作者： Liu, Zibin Xu, Zhezhuang Chen, Jian Cui, Chen Chen, Boyu Zhang, Qingdong College of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Education Fuzhou University Department of Fujian Province Fuzhou350000 China Sansteel Minguang Co. Ltd Fujian Sanming353000 China

ISBN: (纸本)9798350315196

Deducing the twisting pattern of spreader is very important for crane operators in steel warehouse, since crane spreaders have to be rotated repeatedly at steel bar transport sites. To improve the efficiency of the steel bar delivery, the state prediction for crane spreaders is necessary. In order to fulfill this requirement, the HTSK-LN-ReLU model prediction method based on Optuna optimization is applied in this paper. We deploy the IMU on the spreader surface, and then obtain the state data during the operation of the crane spreader by wireless transmission. The data are first denoised through fourier filtering, and then the Optuna framework is used to optimize the HTSK-LN-ReLU model's hyperparameters. The evaluation index of mean square error is used for model evaluation, and finally the optimal hyperparameter combination of the model is selected from 200 comparison experiments. Experimental results demonstrate superior performance of the HTSK-LN-ReLU model in predicting the state of crane spreader for steel bar delivery. © 2023 IEEE.

关键词： Forecasting

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Wood Broken Defect Detection With 3D Laser Scanning

Wood Broken Defect Detection With 3D Laser Scanning

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2022 Chinese automation Congress, CAC 2022

作者： Ai, Zhijie Lin, Ye Xu, Zhezhuang Zhu, Yuhang Wu, Lianxu Fuzhou University School of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China

ISBN: (纸本)9781665465335

Wood broken defects, such as cracks, penetrating dead knots and wanes, will seriously weaken the strength of the wood and destroy the structral integrity of the wood. Therefore, these defects should be inspected and then cut during the production. Although vision-based detection methods have been proposed to detect wood defect regions, they can not detect the defects that change in depth. To solve this problem, this paper focuses on the defect detection by measuring depth difference through 3D laser data. First, the 3D laser data is preprocessed to remove the noise. Secondly, we construct a support profile by multiple mean filtering at the line-level. Next, the residual components are obtained by subtracting the support profile from the profile data and the defect is determined by comparing the residual components and the setting threshold. Finally, we perform merging and filtering operation to determine the final position of defects. The experimental results verify the effectiveness of the proposed method. © 2022 IEEE.

关键词： Defects

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Model-Based Reinforcement Learning for Robotic Arm control with Limited Environment Interaction 13

Model-Based Reinforcement Learning for Robotic Arm Control w...

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13th IEEE International Conference on CYBER Technology in automation, control, and Intelligent Systems, CYBER 2023

作者： Chen, Yi Sun, Xiao Zheng, Song Huang, Weibing Zeng, Sheng Chen, Dan Xu, Zhezhuang College of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou University Education Department of Fujian Province Fuzhou350000 China Evomotion Co. Ltd. Shenzhen Guangdong518000 China

ISBN: (纸本)9798350315196

Reinforcement Learning (RL) has been applied to robotic arm control, which enables the agent to learn an effective policy to solve complex tasks. However, it requires constant interaction with the environment leading to low sample efficiency. In this paper, we propose a robotic arm control approach based on planning via lookahead search, which is a model-based RL algorithm to improve the sample efficiency. The approach builds an environment model in order to obtain the dynamics of the environment. Thus the model can be used to plan future actions by a tree-based search. The experiments show that our approach can solve the task of robotic arm control with less environmental samples. © 2023 IEEE.

关键词： Robotic arms

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Enhancing Scheduling Efficiency of Steel Logistics Parks by Optimized Storage Distribution

Enhancing Scheduling Efficiency of Steel Logistics Parks by ...

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2023 China automation Congress, CAC 2023

作者： Xu, Zhibin Zheng, Song Wang, Jinlong Xu, Zhezhuang Chen, Boyu Zhang, Qingdong College of Electrical Engineering and Automation Fuzhou University Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian Province Fuzhou350000 China Sansteel Minguang Co. Ltd. Sanming353000 China

ISBN: (纸本)9798350303759

The efficient management of storage has become a critical determinant of operational efficiency due to the growing and diverse demand for steel logistics parks. However, the current storage methods consistently result in significant imbalances in the loading of steel products and operating times across multiple yards. To address this challenge, we propose optimizing the distribution of steel products based on demand levels and retrieval efficiency. Firstly, we present an optimization problem that employs demand-driven storage principles to formulate the scheduling of steel product storage. Then, we introduce a novel algorithm called the Adaptive Preferred Evolutionary Heuristic (APEH) to tackle this problem. The results from our experiments indicate that this model effectively enhances the storage structure, and the proposed algorithm consistently yields optimal solutions within a reasonable timeframe. © 2023 IEEE.

关键词： Optimization

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RoboFold: A platform for Protein-folding Inspired Robot Swarms ∗ 5

RoboFold: A platform for Protein-folding Inspired Robot Swar...

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5th World Robot Conference Symposium on Advanced Robotics and automation, WRC SARA 2023

作者： Zhang, Feng Gu, Yuping Yuan, Shuai Yang, Yongliang Shenyang Jianzhu University School of Electrical and Control Engineering Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110016 China Shenyang Jianzhu University School of Computer Science and Engineering School of Electrical and Control Engineering Liaoning Shenyang110168 China

ISBN: (纸本)9798350307320

Natural swarms have inspired various controlling algorithms for swarm robotics, while few of them were programmed in a similar way as the natural swarms. Defining a reliable programming method is still a daunting challenge in swarm robotics. In nature, the information of 3D protein structure is programmed in the sequence of amino acids of the protein. To mimic the programming method of protein folding, we present a platform for investigating protein-folding inspired programming method for robot swarms. This platform includes three parts: a vibration machine, protein-like robot sequences, and recording devices. The preliminary results presented here demonstrated the effectiveness of this platform and the feasibility of protein-folding inspired programming method for robot swarms. © 2023 IEEE.

关键词： Protein folding

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Finite-Time Sideslip Differentiator-Based LOS Guidance for Robust Path Following of Snake Robots

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 239-253页

作者： Yang Xiu Dongfang Li Miaomiao Zhang Hongbin Deng Rob Law Yun Huang Edmond Q.Wu Xin Xu the School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China the School of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Antai College of Economics&Management Shanghai Jiao Tong UniversityShanghai 200240China the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China the Asia-Pacific Academy of Economics and Management University of MacaoMacao 999078China the Department of Decision Science Macao University of Science and TechnologyMacao 999078China the Department of Automation Shanghai Jiao Tong Universityand also with the Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai 200240China the College of Mechatronics and Automation National University of Defense TechnologyChangsha 410073China IEEE

This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake ***,finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track *** proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle *** our method,the designed piecewise auxiliary function guarantees the finite-time stability of position ***,for the case of external disturbances and state constraints,a Barrier Lyapunov functionbased backstepping adaptive path following controller is presented to improve the robot’s *** uniform ultimate boundedness of the closed-loop system is proved by analyzing ***,a gait frequency adjustment-based virtual velocity control input is derived to achieve the exponential convergence of the tangential *** last,the availability and superiority of this work are shown through simulation and experiment results.

关键词： Line-of-sight(LOS) path following sideslip snake robot

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Modeling and Heuristic Solutions for Storage Scheduling of Steel Plates in Steel Logistics Park

Modeling and Heuristic Solutions for Storage Scheduling of S...

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2023 China automation Congress, CAC 2023

作者： Yang, Hao Wang, Jinlong Xu, Zhezhuang Chen, Boyu Zhang, Qingdong College of Electrical Engineering and Automation Key Laboratory of Industrial Automation Control Technology and Information Processing Fuzhou University Education Department of Fujian Province Fuzhou350000 China Sansteel Minguang Co. Ltd. Sanming353000 China

ISBN: (纸本)9798350303759

Steel plates are highly customized according to different customer demands. In this case, the outbound date, the specifications of the steel plates and the distribution of stacks must be simultaneously considered when the steel plates are stored in the yard. Improper storage of steel plates significantly increases the number of shuffles during outbound operations. To overcome the challenge, we propose an efficient steel plate storage scheme based on the actual scenario of existing steel plate distribution in the yard. Firstly, a model for steel plate storage scheduling is established to minimize the number of extra blocking plates. Then, three heuristic algorithms are designed to solve the problem. Comparative experiments are carried out to verify the effectiveness of the proposed algorithm. The experimental results show that the proposed method can sufficiently improve the efficiency of steel plates scheduling. © 2023 IEEE.

关键词： Heuristic algorithms

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Improved electric bike helmet wearing detection algorithm for YOLOv5s 3

Improved electric bike helmet wearing detection algorithm fo...

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3rd International Conference on Artificial Intelligence, Virtual Reality, and Visualization, AIVRV 2023

作者： Han, Lei Niu, Hongxia Key Laboratory of Opt-Electronic Technology and Intelligent Control of Ministry of Education Lanzhou Jiaotong University Lanzhou730070 China Key Laboratory of Plateau Traffic Information Engineering and Control of Gansu Province Lanzhou730070 China School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou730070 China

ISBN: (纸本)9781510671485

Aiming at the problems of low detection accuracy and poor robustness of electric vehicle helmets in complex traffic scenarios, an improved YOLOv5-based electric vehicle helmet detection model is proposed. First, a shallow feature detection layer is added to enable the model to better detect small targets. Then, the attention mechanism is introduced in the backbone network, which optimizes the feature extraction ability of the network. Finally, replacing the CIoU loss function with WIoU improves the convergence speed and regression accuracy. The improved YOLOv5s algorithm was trained and tested on a homemade electric vehicle helmet dataset, and the improved YOLOv5s algorithm improved the average accuracy mean, accuracy rate, and recall rate by 6%, 4%, and 6.7%, respectively, over the original algorithm. The experimental results show that the electric vehicle helmet detection model with improved YOLOv5s algorithm has high helmet detection accuracy, excellent detection of small targets, and strong generalization capability. © 2023 SPIE.

关键词： Signal detection

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