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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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Anti-Sway control of Crane Based on Equivalent-Input-Disturbance Method and Feedback Linearization

Anti-Sway Control of Crane Based on Equivalent-Input-Disturb...

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Chinese control Conference (CCC)

作者： Shuhan He Gang Yu Yongbo Li Fengyu Zhang Wangyong He School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation Complex Systems Wuhan China Huaxin Cement Technology Management (Wuhan) Co. Ltd Wuhan China

The anti-sway issue with crane systems is discussed in this essay. Because cranes are undriveable and nonlinear, implementing anti-sway controllers becomes much more challenging. This work suggests a crane anti-sway controller that uses feedback linearization(FL) in conjunction with the Equivalent-Input-Disturbance (EID) technique to address the issues. to reduce the problem that the feedback linearization largely relies on the model's accuracy. The crane system is first treated as a linear system, after which the unmodeled disturbances, nonlinear components, and external disturbances of the system are treated as the total disturbances of the system, and the effects of these disturbances are then compensated for using disturbance estimation. Finally, simulation experiments confirm that the maximum steady-state fluctuations of the position and angle of the anti-sway controller based on the equivalent input disturbance method and the feedback linearization method are 14 and 6.85 percent, respectively, of those estimated without disturbances. This demonstrates the potency of this approach.

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An Earth Observation Satellite Mission Planning Method Based on Deep Q-Learning 6

An Earth Observation Satellite Mission Planning Method Based...

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6th International Symposium on Computer and Information Processing Technology, ISCIPT 2021

作者： Chen, Tianyuan Wang, Hongfei Liu, Hao Wu, Peng University of Chinese Academy of Sciences Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence Beijing China

ISBN: (纸本)9781665441377

With the increasing number of earth observation satellites and observation demands, satellite mission planning is facing huge challenges. For traditional satellite mission planning methods, there are problems such as difficulty in modeling, high computational complexity, and low scalability. This paper proposes a satellite mission planning method based on Deep Q-Learning. Firstly, a hybrid satellite mission planning model is established that combines the constraint-satisfaction model, the 0-1 knapsack model and the Markov decision model. Then, the decision algorithm based on Deep Q-Learning is used to solve the problem, so that the satellite can make full use of the past mission planning experience to learn the optimal planning strategy. Finally, several traditional satellite mission planning methods-branch and bound algorithm, genetic algorithm, simulated annealing algorithm are compared, and various performances of the algorithms are tested and analyzed through simulation experiments. The superiority of this method is verified. © 2021 IEEE.

关键词： Satellites

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Modeling human travel and social contact with multi-layer networks for epidemic prediction 9

Modeling human travel and social contact with multi-layer ne...

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9th IEEE International Conference on Bioinformatics and Computational Biology, ICBCB 2021

作者： Duan, Wei Wang, Tao Wang, Peng Ju, Rusheng Wang, Xiao Yang, Tian College of Systems Engineering National University of Defense Technology Changsha City China State Key Laboratry of Complex Systems Management and Control Institute of Automation Chinese Academy of Sciences Beijing City China Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha City China

ISBN: (纸本)9780738132020

It is a key issue to reasonably represent human travel and social contact in epidemic models. Various measures were applied to develop the models of human mobility and contact in a long range or a short range, such as Brown movement, random walks, spatial networks, gravity models, contact networks. We proposed a method of representing human daily movement and social contact by using multi-layer networks with temporal edge weights. We combined bipartite networks with social networks to describe human daily trip and social contact, respectively. Temporal edge weights of multi-layer networks were employed to denote the propensity of individual movement and contact. We also verified our models and parameters by incorporating human daily travel and contact regularities, as well as comparing experimental results with human behavior statistical laws. At last, we applied a Chinese university campus as a case study to investigate students' daily travel and social contact, and studied the transmission and control strategies of COVID-19 virus. We found stricter control strategies are needed to mitigate the transmission of COVID-19 virus in a university. Once a patient case emerges in a university, it is better to close the campus and quarantine all students. Partial control strategies such as quarantining a part of students and buildings cannot achieve a great effect of mitigating the transmission of COVID-19 virus. Our works are beneficial for the practitioners in the field of computational epidemiology. © 2021 IEEE.

关键词： Viruses

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Scenario Engineering for Autonomous Transportation: A New Stage in Open-Pit Mines

arXiv

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arXiv 2024年

作者： Teng, Siyu Li, Xuan Li, Yuchen Li, Lingxi Xuanyuan, Zhe Ai, Yunfeng Chen, Long Hong Kong Baptist University Kowloon999077 Hong Kong BNU-HKBU UIC Zhuhai China The Department of Mathematics and Theories Peng Cheng Laboratory Shenzhen518000 China Indianapolis United States Guangdong Provincial Key Laboratory IRADS BNU-HKBU UIC Zhuhai519087 China The University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory of Multimodal Artificial Intelligence Systems The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China WAYTOUS Inc. Beijing100083 China Shenzhen518107 China

In recent years, open-pit mining has seen significant advancement, the cooperative operation of various specialized machinery substantially enhancing the efficiency of mineral extraction. However, the harsh environment and complex conditions in open-pit mines present substantial challenges for the implementation of autonomous transportation systems. This research introduces a novel paradigm that integrates Scenario Engineering (SE) with autonomous transportation systems to significantly improve the trustworthiness, robustness, and efficiency in open-pit mines by incorporating the four key components of SE, including Scenario Feature Extractor, Intelligence and Index, Calibration and Certification, and Verification and Validation. This paradigm has been validated in two famous open-pit mines, the experiment results demonstrate marked improvements in robustness, trustworthiness, and efficiency. By enhancing the capacity, scalability, and diversity of autonomous transportation, this paradigm fosters the integration of SE and parallel driving and finally propels the achievement of the '6S' objectives. Copyright © 2024, The Authors. All rights reserved.

关键词： Efficiency

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Finite-time Robust Fault-tolerant Trajectory Tracking control for QUAVs with Actuator Fault

Finite-time Robust Fault-tolerant Trajectory Tracking Contro...

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Robotics, control and Automation Engineering (RCAE), International Conference on

作者： Rongsheng Xia Chunlei Bu Han Jiang Chery Automobile Stock Limited Company Wuhu China School of Electrical and Information Engineering Anhui University of Technology Ma’Anshan China Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of Technology Ma’Anshan China

ISBN: (数字)9798350355642

ISBN: (纸本)9798350355659

This paper proposed a finite-time robust fault-tolerant trajectory tracking control strategy for quadrotor unmanned aerial vehicles (QUAVs) suffering from actuator saturation, unknown external disturbance and actuator fault. Firstly, robust compensation terms are used to handle unknown external disturbance in position subsystem. On this basis, parameter adaptive method is introduced to remove the adverse effects of actuator saturation in attitude subsystem. Then, a fault detection mechanism is designed to estimate the actuator fault in real time. Subsequently, a finite-time robust fault-tolerant tracking strategy based on backstepping framework are proposed and and the finite-time convergence of all error signals are ensurend. Finally, a numerical simulation result is displayed to validate the effectiveness of the proposed trajectory tracking control scheme for the QUAVs dynamic system.

关键词： Actuators Fault tolerance Trajectory tracking Fault tolerant systems Stability analysis Real-time systems Robots Numerical stability Quadrotors Convergence

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Visual Pencil: Design of Portable Human-Computer Interaction Based on 2D Visual Tracking 17

Visual Pencil: Design of Portable Human-Computer Interaction...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Tong, Ru Wang, Tianzhu Yu, Junzhi Institute of Automation Cas State Key Lab Management and Control for Complex Systems Beijing100190 China

ISBN: (纸本)9781728164151

Convenient and efficient human-computer interaction has always been the goal pursued by researchers. In this paper, we present a vision-based handwriting interaction device for non-touch screens called Visual Pencil. Unlike the conventional interactive method that captures the user's gestures using a motionless visual sensor, Visual Pencil directly mounts the visual sensor in the device. More specifically, the visual data are processed by the feature detection algorithm, and the movement of the pen tip in a 2D plane is calculated, so as to control the cursor and achieve the purpose of interaction. We further define performance indicators for evaluating the design and select more reasonable parameters through specific experiments to achieve the best interaction performance. The experiments verify that the proposed design is able to fulfill the desired operations. The significance of this design lies in that it integrates the functions of the mouse and smart pen, thus removing the requirement of more auxiliary equipment. This work sheds light on the interaction with non-touch screen computers. © 2020 IEEE.

关键词： Human computer interaction

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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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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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Quantifying the impacts of COVID-19 on Sustainable Development Goals using machine learning models

引用

Fundamental Research 2024年第4期4卷 890-897页

作者： Chenyang Shuai Bu Zhao Xi Chen Jianguo Liu Chunmiao Zheng Shen Qu Jian-Ping Zou Ming Xu School of Management Science and Real Estate Chongqing UniversityChongqing 400044China bSchool for Environment and Sustainability University of MichiganAnn ArborMI 489United Stats Michigan Institute for Computational Discovery&Engineering University of MichiganAnn ArborMI 48109United States College of Economics and Management Southwest UniversityChongqing 400044China Center for Systems Integration and Sustainability Department of Fisheries and WildlifeMichigan State UniversityEast LansingMI 48824United States Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control School of Environmental Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China School of Management and Economics Beijing Institute of TechnologyBeijing 100081China Center for Energy&Environmental Policy Research Beijing Institute of TechnologyBejing 100081China Key Laboratory of Jiangxi Province for Persistent Plutants Control and Resources Recycle Nanchang Hangkong UniversityNanchang 330063China Department of Civil and Environmental Engineering University of MichiganAnn ArborMI 48109United States

The COvID-19 pandemic has posed severe threats to global sustainable ***,a comprehensive quantitative assessment of the impacts of COVID-19 on Sustainable Development Goals(SDGs)is still *** research quantified the post-COVID-19 SDG progress from 2020 to 2024 using projected GDP growth and population and machine learning models including support vector machine,random forest,and extreme gradient *** results show that the overall SDG performance declined by 7.7%in 2020 at the global scale,with 12 socioeconomic SDG performance decreasing by 3.0%-22.3%and 4 environmental SDG performance increasing by 1.6%-9.2%.By 2024,the progress of 12 SDGs will lag behind for one to eight years compared to their pre-COVID-19 trajectories,while extra time will be gained for 4 environment-related ***,the pandemic will cause more impacts on countries in emerging markets and developing economies than those on advanced economies,and the latter will recover more quickly to be closer to their pre-covID-19 trajectories by ***-COVID-19 economic recovery should emphasize in areas that can help decouple economic growth from negative environmental *** results can help government and non-state stakeholders identify critical areas for targeted policy to resume and speed up the progress to achieve SDGs by 2030.

关键词： Sustainable development goals COVID-19 Machine learning Global development Sustainable development assessment

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