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43rd Chinese control Conference, CCC 2024

作者： Yang, Qingru Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Recently, the use of neural radiance fields (NeRF) for three-dimensional reconstruction of humans has achieved high-quality view rendering. However, existing methods often rely on multiple or single videos as input, requiring dense images, and the rendering quality tends to be poor with sparse image inputs. To address this issue, this paper proposes a novel method that solely utilizes sparse images captured by a single camera to create an animatable human neural radiance field, enabling the rendering of high-fidelity human images under arbitrary novel viewpoints and poses. Specifically, our method utilizes body poses and multi-view feature to build a deformable neural radiance field, and employs frequency-segmented positional encoding to mitigate overfitting during training process. Extensive quantitative and qualitative experiments demonstrate that our proposed method outperforms prior works. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Image reconstruction

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Integrated Prediction of Unfavorable Geology in Main Tunnel Considering the Geological Conditions of Parallel Tunnel

Integrated Prediction of Unfavorable Geology in Main Tunnel ...

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2024 China Automation Congress, CAC 2024

作者： Zhang, Meng Gan, Chao Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350368604

Currently, the advanced geological prediction for the main tunnel from the parallel tunnel often employs parallel deduction of detection conclusions, which faces issues such as a lack of diverse geological exploration information, a lack of analysis of geological structures and poor accuracy. In this paper, an integrated prediction method for unfavorable geology in main tunnel considering the geological conditions of parallel tunnel is proposed, which consists of three stages. In the first stage, based on the forecast mileage range and tunnel excavation conditions, the process is divided into four specific cases. In the second stage, it deduces the geology of the main tunnel along the orientation of rock strata occurrence or joint to parallel tunnel and selects the results of the rock strata occurrence or joint deduction according to the distance of the deduction. In the last stage, it deduces the geological conditions of parallel tunnel face and the integration of geophysical and drilling information for predictive conclusions based on the four specific cases. The proposed method offers higher prediction accuracy for rock mass integrity and surrounding rock grades compared to parallel deduction method. © 2024 IEEE.

关键词： Miocene

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3D Object Pose Estimation Based on End-to-End Differentiable Perspective Projection 43

3D Object Pose Estimation Based on End-to-End Differentiable...

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43rd Chinese control Conference, CCC 2024

作者： Cai, Yuheng Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Locating 3D objects from a single RGB image via perspective projection is a long-standing problem in computer vision. Inspired by differentiable geometry methods in the field of camera relocation, we apply this neural network combined with differentiable perspective projection to form an end-to-end architecture to the field of object position estimation through object 3D reconstruction methods. The proposed method uses a differentiable LM algorithm for end-to-end pose estimation to achieve higher accuracy, and the gradient is passed back to the neural network to guide its learning. At the same time, we propose a virtual view generation algorithm for augmenting the data to improve the algorithm's sensitivity to the size of the co-vision region. Through experiments, we prove the effectiveness of our method. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Neural networks

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Autonomous Underwater Vehicle Localization and Map Building Based SVSF Using Smoothing Boundary Layer Width 5th

Autonomous Underwater Vehicle Localization and Map Building...

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5th International Conference on Electrical Engineering and control Applications, ICEECA 2022

作者： Demim, Fethi Bouzerzour, Hamza Rouigueb, Abdenebi Benghezal, Amar Allam, Ahmed Nemra, Abdelkrim Gauiatni, Mohamed Kobzili, Elhaouari Bazoula, Abdelouahab Guidance and Navigation Laboratory Ecole Militaire Polytechnique EMP Bordj El Bahri Algiers Algeria Complex Systems Control and Simulators Laboratory Ecole Militaire Polytechnique EMP Bordj El Bahri Algiers Algeria Optimization Techniques Laboratory Ecole Militaire Polytechnique EMP Bordj El Bahri Algiers Algeria

ISBN: (纸本)9789819700448

Localization technology is one of the most crucial issues for underwater vehicle applications that must accomplish any scheduled task in the challenging aquatic environment. Simultaneous Localization and Mapping (SLAM) with an Autonomous Underwater Vehicle (AUV) is currently a hot topic in the study. UAVs have only recently achieved greater recognition, and underwater platforms are still being studied. An approach has been established to ensure the success of an accurate localization mission by overcoming the problem of drifting from an AUV’s planned trajectory. A new adaptive technique based on two merged filters, Smooth Variable Structure Filter (SVSF) and Extended Kalman Filter (EKF), is presented to increase the accuracy of AUV localization. The accuracy, stability, and reduction in terms of Root Mean Square Error (RMSE) of the localization position of the AUV have been tested in natural conditions using the results of several experiments. These experimental data are used in the SLAM algorithm, which shows the best result and performance using the proposed approach compared to other algorithms. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Extended Kalman filters

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Manual Alignment of Dual End-Effectors for Piezo-Driven Microhand

Manual Alignment of Dual End-Effectors for Piezo-Driven Micr...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Pang, Jichao Liu, Dan Tang, Xiaoqing Chen, Yan Huang, Qiang Arai, Tatsuo Liu, Xiaoming Key Laboratory of Biomimetc Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Advanced Innovation Center for Intelligent Robots and Systems School of Mechatronical Engineerin Beijing Institute of Technology Beijing100081 China The University of Electro-Communications Center for Neuroscience and Biomedical Engineering Tokyo182-8585 Japan

ISBN: (纸本)9798350372601

In recent years, micromanipulator with dual end-effectors called microhand has been widely used in industrial and biological fields. Whether the tip positions of the two end-effectors of the microhand can be accurately aligned seriously affects the precise grasping of the microhand. However, few researchers have presented practical ways for precisely aligning the tip positions of a 6-DOF microhand's two end- effectors. This paper proposes a novel, inexpensive, lightweight, robust, and easy-to-use microhand dual end-effectors clamping device that can precisely and quickly align the two end-effectors of a 6-DOF microhand. First, we describe the microhand dual end-effectors clamping device's lightweight structural design. After that, we simplify the microhand dual end-effectors clamping device model and create a mathematical model to determine the relationship between the end-effectors' tip position and the rotation angles of screw No.1, screw No.2, screw No.3 of the microhand dual end-effectors clamping device. Through experimentation, we are able to attain precise alignment of the two end-effectors tip positions of the 6-DOF microhand, so we confirm that our mathematical model is true. Finally, we use the impulse response of PZT in the microhand's lower module to confirm the stability of the microhand dual end- effectors clamping device. We believe that the proposed the microhand dual end-effectors clamping device has great potential in industrial and biological applications as a universal tool for precise alignment of the tip positions of the two end-effectors of a 6-DOF microhand. © 2024 IEEE.

关键词： Clamping devices

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Parallel Learning:Overview and Perspective for Computational Learning Across Syn2Real and Sim2Real

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 603-631页

作者： Qinghai Miao Yisheng Lv Min Huang Xiao Wang Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Artificial Intelligence Anhui UniversityHefei 266114China Qingdao Academy of Intelligent Industries Qingdao 230031China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

The virtual-to-real paradigm,i.e.,training models on virtual data and then applying them to solve real-world problems,has attracted more and more attention from various domains by successfully alleviating the data shortage problem in machine *** summarize the advances in recent years,this survey comprehensively reviews the literature,from the viewport of parallel ***,an extended parallel learning framework is proposed to cover main domains including computer vision,natural language processing,robotics,and autonomous ***,a multi-dimensional taxonomy is designed to organize the literature in a hierarchical ***,the related virtual-toreal works are analyzed and compared according to the three principles of parallel learning known as description,prediction,and prescription,which cover the methods for constructing virtual worlds,generating labeled data,domain transferring,model training and testing,as well as optimizing the strategies to guide the task-oriented data generator for better learning *** issues remained in virtual-to-real are ***,the future research directions from the viewpoint of parallel learning are suggested.

关键词： Machine learning parallel learning parallel systems sim-to-real syn-to-real virtual-to-real

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Prediction of photovoltaic power generation based on LSTM and transfer learning digital twin

Prediction of photovoltaic power generation based on LSTM an...

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International Conference on Emerging Electronic and Automation Technology 2022, ICEEAT 2022

作者： Yang, Heng Wang, Weisong School of Mathematics and Statistics Qiannan Normal University for Nationalities 558000 China School of Computer Sciences Baoji University of Arts and Sciences 721007 China Laboratory of Complex Systems and Intelligent Optimization of Guizhou Duyun Guizhou558000 China

This research offers a digital twin model for solar power production power prediction based on long short term memory network (LSTM), and then applies this model to other models with limited operational time and inadequate data through transfer learning. The prediction for the solar system's electrical output. Due to the effect of sun irradiation, temperature, and other random elements, photovoltaic power output is very intermittent and fluctuating, making it impossible to anticipate photovoltaic power with precision. Synchronization and real-time updating of physical entities, thereby obtaining more accurate forecasting results than traditional forecasting methods, while utilizing knowledge learned from PV systems with sufficient historical data to assist PV systems with limited historical data in establishing a digital twin of power generation forecasting model, not only can obtain accurate prediction results but also save training time for the model. In this study, the PV historical data of three distinct sites from the open source websites of Queensland University and Shanxi Jinneng Clean Energy Company are used to validate the validity of the suggested technique. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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Analysis of LoRa for Electronic Shelf Labels Based on Distributed Machine Learning 42

Analysis of LoRa for Electronic Shelf Labels Based on Distri...

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42nd Chinese control Conference, CCC 2023

作者： Khan, Malak Abid Ali Ma, Hongbin Jin, Ying Ma, Jingxiang Rehman, Zia Ur Rahman, Mizanur School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

Deforestation is the primary source of global warming;traditional shelf labels use paper to display the price of the products, and human forces play a pivotal role in updating the tags where the pandemic has strictly limited its power. Various technologies provide connectivity and a fast-updating system to eliminate the paper-based approach. LoRa is one of the contenders to design the system for electronic shelf labels (ESLs). In this paper, LoRa has been used to minify data losses and guarantee the successful decoding of the carrier signals. The data parallelism at the network server (NS) is used to distribute the data packets among the gateways (GWs) for concurrent transmissions to the end devices (EDs). The EDs are placed in different ranges using machine clustering to avoid intra-SF interference and collision. The data rate (DR) and spreading factors (SFs) have been proposed to improve the performance of pure and slotted ALOHA for the properly allocated tags. The orthogonality principles follow industrial, scientific, and medical regulations (ISM) to avoid data traffic congestion. GWs under different duty cycles (DC) and bandwidth (BW) are examined to minify the network saturation and reduce the energy harvesting of the tags. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Deforestation

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Lane-Change Intention Prediction of Surrounding Vehicles Using BiLSTM-CRF Models with Rule Embedding

Lane-Change Intention Prediction of Surrounding Vehicles Usi...

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2022 Chinese Automation Congress, CAC 2022

作者： Wang, Kai Hou, Jie Zeng, Xianlin School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9781665465335

Predicting lane-change intentions of surrounding vehicles can effectively help autonomous vehicles reduce collisions caused by lane changes and ensure driving safety. Because prediction methods based on black-box models will lead to passengers' distrust of machine prediction, the intention prediction methods used to autonomous driving need to be interpretable and trustworthy. This paper presents a method for intention prediction of surrounding vehicles by using a bidirectional long short term memory network (BiLSTM) with a conditional random field (CRF) layer above it. Compared with intention prediction methods using deep network, the proposed method can find the features that contribute most to the prediction, thereby improving the interpretability and ensuring the prediction performance. In addition, by employing the transfer characteristic of the CRF layer, traffic rules and the experience of skilled drivers can be embedded to the prediction in the form of rules. Use rules to constrain the intention prediction, thereby improving the trustworthiness of prediction results. Test results on naturalistic driving dataset show that the proposed method can predict the lane-change intention with an accuracy of 97.22%, which is higher than that of Bi-LSTM. © 2022 IEEE.

关键词： Embeddings

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Unified Addressing Algorithm for Tasks in Cloud control systems 41

Unified Addressing Algorithm for Tasks in Cloud Control Syst...

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第41届中国控制会议

作者： Guan Wang Yufeng Zhan Yuanqing Xia Liping Yan Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology School of Information Science and Engineering University of ZaoZhuang

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the rapid development of cloud computing and control theory,a new paradigm of networked control systems named cloud control systems has been proposed to satisfy the requirements of large-scale and complex *** is critical to manage large-scale tasks with personalized needs on the large number of heterogeneous ***,current TCP/IPbased addressing approach does not consider the runtime constraints of tasks,resulting highly concurrent service search,and communication between tasks will become the system *** this paper,we propose a task property encoding method which takes multi-dimensional properties into *** on the proposed encoding method,we design a uniform addressing method for tasks in the ***,we experimentally demonstrate the effectiveness of task property encoding,and the unified addressing method for tasks is more effective than other methods in the case of high task concurrency.

关键词： Cloud control systems address encoding cloud-edge-device cooperation

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