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A modified YOLOv4 detection method for a vision-based underwater garbage cleaning robot

Frontiers of Information Technology & Electronic Engineering 2022年第8期23卷 1217-1228页

作者： Manjun TIAN Xiali LI Shihan KONG Licheng WU Junzhi YU First Research Institute of the Ministry of Public Security of PRC Beijing 100048China School of Information Engineering Minzu University of ChinaBeijing 100081China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

To tackle the problem of aquatic environment pollution,a vision-based autonomous underwater garbage cleaning robot has been developed in our *** propose a garbage detection method based on a modified YOLOv4,allowing high-speed and high-precision object ***,the YOLOv4 algorithm is chosen as a basic neural network framework to perform object *** the purpose of further improvement on the detection accuracy,YOLOv4 is transformed into a four-scale detection *** improve the detection speed,model pruning is applied to the new *** virtue of the improved detection methods,the robot can collect garbage *** detection speed is up to 66.67 frames/s with a mean average precision(mAP)of 95.099%,and experimental results demonstrate that both the detection speed and the accuracy of the improved YOLOv4 are excellent.

关键词： Object detection Aquatic environment Garbage cleaning robot Modified YOLOv4

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Numerical and Experimental Research on Electromagnetic-Thermal and Leakage Defects Characteristics of the High Voltage Cable Terminal

SSRN

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SSRN 2023年

作者： Liu, Xingmou Gu, Yan Li, Lei Yang, Yongming Cheng, Peng Jadoon, Ammad Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing400044 China State Grid Sichuan Electric Power Company Chengdu Power Supply Company Chengdu610000 China NFC-Institute of Engineering &Technology Multan Pakistan

Thermal and insulation performance of the High Voltage Cable Terminal (HVCT) could effectively improve the reliability and economy of power energy transmission. In this paper, a numerical model of the electromagnetic heat flow field was proposed to analyze the heat transfer and temperature characteristics of HVCT under oil leakage defects. This model was the first validated using operation data from the actual equipment and the relative error was less than 1.51%. The effects of oil leakage fault on the global and local temperature distribution of the HVCT were then investigated under different load currents. In addition, the local temperature rise effect of different ambient temperatures on the HVCT oil leakage defect was also considered. Finally, combined with reference indicators such as oil level, temperature, and temperature gradient, a qualitative and quantitative evaluation of the oil leakage fault of HVCT was performed. The results showed that the temperature of the core, surface, and their maximum temperature gradient were linearly related to the ambient temperature. However, the temperature of the core at the oil leak exceeded the normal temperature by up to 7.2 °C with 1000A load current, and the temperature gradient change reaches 681.3 °C/m, which indicated that the convection heat dissipation effect of the oil-deficient part was poor, and the heat accumulates near the cable core. Therefore, the numerical model and analytical results presented in this paper provided an important method for online temperature monitoring and fault analysis of HVCTs. © 2023, The Authors. All rights reserved.

关键词： Thermal gradients

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Parallel Learning Based Foundation Model for Networked Traffic Signal control

Parallel Learning Based Foundation Model for Networked Traff...

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International Conference on Intelligent Transportation

作者： Chen Zhao Xingyuan Dai Yuanyuan Chen Yilun Lin Yisheng Lv Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Shanghai AI Laboratory Shanghai China Macao Institute of Systems Engineering Macau University of Science and Technology Macao China

Networked Traffic Signal control (NTSC) is a fundamental component of Intelligent Transportation systems (ITS) and the broader vision of smart city development. While a plethora of intelligent strategies have been developed, the Sim2Real challenge often impedes their full realization. In response, this paper introduces the Parallel Learning-based Adaptive Network for Traffic Signal control (PLANT) as a foundation model for NTSC. We employ the Wasserstein GAN with Gradient Penalty (WGAN-GP) to generate a wide range of artificial scenarios for robust PLANT training. Further, the Transformer-based Cooperation Mechanism (TCM) is integrated as the primary learner within PLANT, facilitating effective capture of traffic dynamics and knowledge accumulation. This knowledge is readily transferable to real-world applications through meticulous fine-tuning, equipping PLANT to adapt and evolve in alignment with shifting transportation paradigms. Our empirical study on the Hangzhou road network demonstrates PLANT's superiority over both traditional and emerging DRL-based approaches, emphasizing its viability as a potential foundation model for NTSC.

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Zero-Sum Differential Game-Based Fault-Tolerant Tracking control for Nonlinear systems With Multiplicative Failures

Zero-Sum Differential Game-Based Fault-Tolerant Tracking Con...

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Chinese Automation Congress (CAC)

作者： Cong Tan Mingduo Lin Hongbing Xia Bo Zhao Yancai Xu School of Systems Science Beijing Normal University Beijing China Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

A novel fault-tolerant tracking control (FTTC) approach for affine nonlinear systems is developed from the perspective of zero-sum differential games (ZSDG) to deal with unknown multiplicative actuator failures in this paper. By regarding the control input and the multiplicative actuator failure as two players of a zero-sum game, a performance index function reflecting the trajectory tracking error, the control policy and the unknown failure is established. To handle the tracking Hamilton-Jacobi-Isaacs (HJI) equation associated with the established performance index function, a critic neural network is utilized. Then, the Nash equilibrium solution can be obtained, and the FTTC is achieved. The stability of the faulty nonlinear system is examined through Lyapunov-based approach. Finally, simulation results of a spring system is provided to ensure the utility and the realizability of the ZSDG-based FTTC approach.

关键词： Actuators Fault tolerance Trajectory tracking Simulation Fault tolerant systems Stability criteria Mathematical models

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Target Assignment Optimization of Heterogeneous Sensor Networks in Urban Environment 39

Target Assignment Optimization of Heterogeneous Sensor Netwo...

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39th Chinese control Conference, CCC 2020

作者： Chen, Chen Zihao, Cheng Wei, Xu Beijing Institute of Technology School of Automation Beijing100081 China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing100081 China

ISBN: (纸本)9789881563903

Preventing and controlling Low-Slow-Small(LSS) targets are problems to be solved due to their good concealment in urban environment. Consequently, the problem of target assignment is studied in this paper. Firstly, a target assignment model based on heterogeneous sensor networks is proposed. The characteristics of LSS targets and the influence of environmental factors such as climate and terrain are considered on this model. At the same time, the detection capabilities of different detection nodes and collaborative tracking capabilities are also considered. Secondly, an intelligent optimization algorithm GSAPSO based on PSO is proposed to maximize tracking effect of the sensors. Finally, the simulations are used to compare the GSAPSO algorithm with the traditional PSO and GAPSO algorithms. The results demonstrate that the proposed algorithm has better tracking effect. © 2020 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Particle swarm optimization (PSO)

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Remote Operation with Haptic Force and Virtual Proxy for an Underwater Vehicle-Manipulator system 10

Remote Operation with Haptic Force and Virtual Proxy for an ...

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10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Ma, Jin Wang, Yu Wang, Rui Wang, Shuo University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Cas Center for Excellence in Brain Science and Intelligence Technology Shanghai200031 China

ISBN: (纸本)9781665424233

This paper aims to investigate a smooth teleoperation method for the underwater vehicle-manipulator system. First, a coordinated mapping control method for the vehicle is presented. The haptic force is considered to help assist the operation. Then, two mapping modes are used to teleoperate the manipulator: when the end-effector needs to move in a large area, two virtual points and a spring-damping system are implemented to filter the operator's hand jitter and limit the manipulator's speed;when the end-effector needs to move in a small area, a position increment control method with a small proportional coefficient is used to improve the precision. Finally, the simulation demonstrates the effectiveness of the proposed teleoperation method. © 2021 IEEE.

关键词： Manipulators

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Artificial intelligence in gastric cancer:applications and challenges

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Gastroenterology Report 2022年第1期10卷 227-242页

作者： Runnan Cao Lei Tang Mengjie Fang Lianzhen Zhong Siwen Wang Lixin Gong Jiazheng Li Di Dong Jie Tian School of Artificial Intelligence University of Chinese Academy of SciencesBeijingP.R.China CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imagingthe State Key Laboratory of Management and Control for Complex SystemsInstitute of AutomationChinese Academy of SciencesBeijingP.R.China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Radiology DepartmentPeking University Cancer Hospital&InstituteBeijingP.R.China College of Medicine and Biological Information Engineering School Northeastern UniversityShenyangLiaoningP.R.China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Engineering MedicineBeihang UniversityBeijingP.R.China Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education School of Life Science and TechnologyXidian UniversityXi’anShaanxiP.R.China

Gastric cancer(GC)is one of the most common malignant tumors with high *** diagnosis and treatment decisions for GC rely heavily on human experts’careful judgments on medical ***,the improvement of the accuracy is hindered by imaging conditions,limited experience,objective criteria,and inter-observer ***,the developments of machine learning,especially deep-learning algorithms,have been facilitating computers to extract more information from data *** are exploring the far-reaching applications of artificial intelligence(AI)in various clinical practices,including ***,we aim to provide a broad framework to summarize current research on AI in *** the screening of GC,AI can identify precancerous diseases and assist in early cancer detection with endoscopic examination and pathological *** the diagnosis of GC,AI can support tumor-node-metastasis(TNM)staging and subtype *** treatment decisions,AI can help with surgical margin determination and prognosis ***,current approaches are challenged by data scarcity and poor *** tackle these problems,more regulated data,unified processing procedures,and advanced algorithms are urgently needed to build more accurate and robust AI models for GC.

关键词： gastric cancer artificial intelligence radiomics endoscopy computed tomography pathology

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NVIF: Neighboring Variational Information Flow for Large-Scale Cooperative Multi-Agent Scenarios

arXiv

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arXiv 2022年

作者： Chai, Jiajun Zhu, Yuanheng Zhao, Dongbin The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

Communication-based multi-agent reinforcement learning (MARL) provides information exchange between agents, which promotes the cooperation. However, existing methods cannot perform well in the large-scale multi-agent system. In this paper, we adopt neighboring communication and propose a Neighboring Variational Information Flow (NVIF) to provide efficient communication for agents. It employs variational autoencoder to compress the shared information into a latent state. This communication protocol does not rely dependently on a specific task, so that it can be pre-trained to stabilize the MARL training. Besides. we combine NVIF with Proximal Policy Optimization (NVIF-PPO) and Deep Q Network (NVIFDQN), and present a theoretical analysis to illustrate NVIFPPO can promote cooperation. We evaluate the NVIF-PPO and NVIF-DQN on MAgent, a widely used large-scale multi-agent environment, by two tasks with different map sizes. Experiments show that our method outperforms other compared methods, and can learn effective and scalable cooperation strategies in the large-scale multi-agent system. Copyright © 2022, The Authors. All rights reserved.

关键词： Reinforcement learning

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Parallel control for Continuous-Time Linear systems:A Case Study

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 919-928页

作者： Qinglai Wei Hongyang Li Fei-Yue Wang the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the University of Chinese Academy of Sciences Beijing 100049 Qingdao Academy of Intelligent Industries Qingdao 266109China the Institute of Systems Engineering Macao University of Science and Technology

In this paper,a new parallel controller is developed for continuous-time linear *** main contribution of the method is to establish a new parallel control law,where both state and control are considered as the *** structure of the parallel control is provided,and the relationship between the parallel control and traditional feedback controls is *** the situations that the systems are controllable and incompletely controllable,the properties of the parallel control law are *** parallel controller design algorithms are given under the conditions that the systems are controllable and incompletely ***,numerical simulations are carried out to demonstrate the effectiveness and applicability of the present *** Terms-Continuous-time linear systems,digital twin,parallel controller,parallel intelligence,parallel systems.

关键词： Index Terms—Continuous-time linear systems digital twin parallel controller parallel intelligence parallel systems

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Research on the High-Precision Unmanned Operation control Algorithm of theVibroseis Vehicle

Research on the High-Precision Unmanned Operation Control Al...

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第40届中国控制会议

作者： LI Bin WANG Shoukun WANG Shuai WANG Junzheng LIU Shangfei State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology Beijing Institute of Technology

In order to meet the demand for high-precision operation of the vibroseis vehicle in the case of unmanned driving, an unmanned operation system that meets the working characteristics of the vibroseis vehicle is designed, and the key technical problems are studied, so that the vibroseis vehicle can operate in the complex environment of the field and improve the efficiency of geological exploration greatly. Firstly, the coordinate system and the kinematic model without sideslip of the articulated vehicle are established successively. Secondly, in order to improve the path tracking accuracy of the vibroseis vehicle, a model predictive control algorithm based on the kinematic model is designed for vehicle path tracking. In order to improve the positioning accuracy of the working point, a compensation algorithm for positioning error is proposed to reduce the positioning error caused by terrain factors. Finally, the unmanned operation platform is built and the path tracking algorithm and the compensation algorithm for positioning error are verified on the platform. The real vehicle test data shows that the path tracking algorithm proposed in this paper can control the average lateral error of the path tracking of the vibroseis vehicle within 22 *** with the PID control method, its path tracking accuracy can be improved by 59%. The average positioning error of working point is controlled within about 15 cm by adopting the compensation algorithm for positioning error.

关键词： Vibroseis vehicle Unmanned operation Path tracking Positioning compensation

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