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SSRN 2023年

作者： Li, Ziyu Yao, Yuncong Quan, Zhibin Qi, Lei Feng, Zhenhua Yang, Wankou School of Automation Southeast University Nanjing210096 China Key Lab of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China School of Computer Science and Engineering Southeast University Nanjing210096 China Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom

LiDAR-based 3D detectors perform well on particular autonomous driving benchmarks, but may poorly generalize to other domains. Existing 3D domain adaptive detection methods usually require annotation-related statistics or continuous refinement of pseudo-labels. The former is not always feasible for practical applications, while the latter lacks sufficient accurate supervision. In this work, we propose a novel unsupervised domain adaptive framework, namely Adaptation Via Proxy (AVP), that explicitly leverages cross-domain relationships to generate adequate high-quality samples without any target statistics, thus mitigating domain shifts for existing LiDAR-based 3D detectors. Specifically, we first train the detector on the source domain with curriculum example mining to enhance its generalization capability. Then, we fine-tune the pre-trained detector on the instance-aware proxy that is a data collection with stronger supervision. The instance-aware proxy utilizes the profitable instances from the source domain to provide more robust supervision for optimizing the detector to overcome domain gaps. Note that AVP is architecture-agnostic thus it can be easily injected with any LiDAR-based 3D detectors. Extensive experiments on Waymo, nuScenes, KITTI and Lyft demonstrate the superiority of the proposed method over the state-of-the-art approaches for different adaptation scenarios. © 2023, The Authors. All rights reserved.

关键词： Object detection

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A Power Split Strategy for a Vehicular Hybrid Energy Storage System Using Adaptive Neuro Fuzzy Inference System

A Power Split Strategy for a Vehicular Hybrid Energy Storage...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Jiao Li Lijun Zhang Longzhi Yang Bo Wang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Wuhan China Department of Computer Science and Digital Technologies Faculty of Engineering and Environment Northumbria University Newcastle upon Tyne U.K

This paper presents a real-time power split strategy for a battery-supercapacitor hybrid energy storage system. The objective of the proposed strategy is to alleviate battery degradation through effective supercapacitor utilization. The proposed strategy employs an adaptive neural fuzzy inference system, which is capable of learning a power split strategy from offline optimization results and distributing power in real-time. The performance of the strategy proposed and a low pass filtering technique is compared through simulations. The results demonstrate that the proposed method can effectively reduce battery capacity loss and perform well under unknown driving cycles in real time.

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Selecting fundamental and equipment of valve tappet

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Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 2010年第8 SUPPL.期31卷 157-161页

作者： Xu, Lianhu Yuan, Yibao Gong, Guangguo Department of Automation Measurement and Control Engineering Harbin Institute of Technology Harbin 150001 China Harbin High Tech. Precision Gage Co. Ltd. Harbin 150060 China

The valve clearance is essential to the engine efficacy, this paper presents the definition of the valve clearance and selecting fundamental of the valve tappet, and the tappet selector was developed on these grounds, which was consisted of the cylinder head measurement machine and camshaft measurement machine;the errors of the tappet selector were analyzed in brief, and the repetition and veracity of the tappet selector were tested, the data shows that the measurement is accurate, the valve clearance could be controlled with the tappet selector.

关键词： Automotive engineering

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A Multi-population Integrated Approach for Capacitated Location Routing

arXiv

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arXiv 2024年

作者： He, Pengfei Hao, Jin-Kao Wu, Qinghua School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China Department of Computer Science LERIA University of Angers 2 Boulevard Lavoisier Angers49045 France School of Management Huazhong University of Science and Technology No. 1037 Luoyu Road Wuhan China

The capacitated location-routing problem involves determining the depots from a set of candidate capacitated depot locations and finding the required routes from the selected depots to serve a set of customers whereas minimizing a cost function that includes the cost of opening the chosen depots, the fixed utilization cost per vehicle used, and the total cost (distance) of the routes. This paper presents a multi-population integrated framework in which a multi-depot edge assembly crossover generates promising offspring solutions from the perspective of both depot location and route edge assembly. The method includes an effective neighborhood-based local search, a feasibility-restoring procedure and a diversification-oriented mutation. Of particular interest is the multi-population scheme which organizes the population into multiple subpopulations based on depot configurations. Extensive experiments on 281 benchmark instances from the literature show that the algorithm performs remarkably well, by improving 101 best-known results (new upper bounds) and matching 84 best-known results. Additional experiments are presented to gain insight into the role of the key elements of the algorithm. © 2024, CC BY-NC-ND.

关键词： Cost functions

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DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatial and Temporal Transformer Network

DSTFormer: 3D Human Pose Estimation with a Dual-scale Spatia...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Shaokun Zhang Xinde Li Chuanfei Hu Jianping Xu Huaping Liu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Nanjing Center for Applied Mathematics Nanjing China Southeast University Shenzhen Research Institute Shenzhen China Science and Technology on Information Systems Engineering Laboratory Nanjing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Recent transformer-based methods for estimating 3D human pose have gained widespread attention, achieving state-of-the-art results. Previous methods have primarily focused on capturing motion patterns of the human body at a single scale or cascading multiple scales, such as joints, bones, and body-parts. However, they are difficult to simultaneously capture spatial-temporal motion patterns of the human body at different scales due to the complex motion patterns. To address this issue, we propose Dual-scale Spatial and Temporal transFormer (DSTFormer), which can concurrently explore the spatial dependencies and temporal motion patterns of human joints and bones. Additionally, we introduce a Gcn-Spatial Transformer Block (GSTB), which introduces Graph Convolutional Networks (GCN) into transformer to enhance the exploitation of local relationships and global information between adjacent joints or bones. Extensive experiments are conducted on the Human3.6M benchmark dataset, and superior results are reported when comparing to other state-of-the-art methods. More remarkably, our model achieves to-date the best published performance, with P1 errors of 37.9 mm and 15.6 mm, respectively.

关键词： Solid modeling Three-dimensional displays Mechatronics Graph convolutional networks Computational modeling Pose estimation Transformers Bones Joints Robots

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Optimization of Directional Landmark Deployment for Visual Observer on SE(3)

arXiv

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arXiv 2022年

作者： Lei, Zike Chen, Xi Tan, Ying Chen, Xiang Chai, Li The School of Information Science and Engineering Wuhan University of Science and Technology Hubei 430081 China The Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan University of Science and Technology Hubei 430081 China The School of Electrical Mechanical and Infrastructure Engineering The University of Melbourne VIC3010 Australia The Department of Electrical and Computer Engineering University of Windsor ONN9B 3P4 Canada The College of Control Science and Engineering Zhejiang University Hangzhou310027 China

An optimization method is proposed in this paper for novel deployment of given number of directional landmarks (location and pose) within a given region in the 3-D task space. This new deployment technique is built on the geometric models of both landmarks and the monocular camera. In particular, a new concept of Multiple Coverage Probability (MCP) is defined to characterize the probability of at least n landmarks being covered simultaneously by a camera at a fixed position. The optimization is conducted with respect to the position and pose of the given number of landmarks to maximize MCP through globally exploration of the given 3-D space. By adopting the elimination genetic algorithm, the global optimal solutions can be obtained, which are then applied to improve the convergent performance of the visual observer on SE(3) as a demonstration example. Both simulation and experimental results are presented to validate the effectiveness of the proposed landmark deployment optimization method. © 2022, CC BY-NC-SA.

关键词： Probability

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Design and Implementation of Adaptive NMPC in industrial applications: case study

Design and Implementation of Adaptive NMPC in industrial app...

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International Carpathian control Conference (ICCC)

作者： Stepan Ozana Filip Krupa Jakub Nemcik Gergely Takacs Jakub Mozaryn Petr Beremlijski Abhaya Singh Aleksandra Kawala-Sterniuk Department of Cybernetics and Biomedical Engineering VSB-Technical University of Ostrava Ostrava Czech Republic Institute of Automation Measurement and Applied Informatics Slovak University of Technology in Bratislava Bratislava Slovak Republic Institute of Automatic Control and Robotics Warsaw University of Technology Warsaw Poland Department of Applied Mathematics VSB-Technical University of Ostrava Ostrava Czech Republic Department of engineering University of Sannio Sannio Italy Department of Electrical Power and Renewable Energy Opole University of Technology Opole Poland

This paper deals with the design and implementation of adaptive nonlinear predictive control (NMPC). The resulting control system is deployed on a softPLC embedded target in real-time via the REXYGEN control system. The paper describes functional prototype using softPLC hosting the NMPC algorithm applied for a nonlinear system consisting of three coupled tanks. The NMPC algorithm is solved via the receding horizon control method (RHC), formulated as a nonlinear programming problem (NLP) and numerically computed using the SOLNP solver. The adaptivity is provided by online identification via moving horizon estimation (MHE), keeping the model updated to avoid a model-plant mismatch. The methodology described in this paper can be easily transferred to a wider group of industrial nonlinear processes. Such created control unit can run in a standalone mode or can be connected to some exiting control system providing a necessary computational power and thus upgrading the quality of control significantly.

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Design of User Plane in 5G Core Network Based on SDN

Design of User Plane in 5G Core Network Based on SDN

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IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC)

作者： Ping Wang Zhan Xu Ming Zhao Zhao Liu Yi Gong School of Automation Beijing Information Science and Technology University Beijing China Ministry of Education Key Laboratory of Modern Measurement & Control Technology Beijing Information Science and Technology University Beijing China Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China Department of Electronic Engineering Tsinghua University Beijing China

With the rapid increase in demand for the fifth-generation mobile communication technology (5G) in the BusinesstoBusiness (ToB) market, future factories, especially those involving a large number of Internet of Things (IoT) devices, will prioritize deploying private networks to achieve prioritized scheduling, resource allocation, and security control over the entire network. The User Plane Function (UPF) is an important network element in the 5G core network. In practical deployments, UPF typically uses dedicated hardware devices, which are not only expensive but also have a tightly coupled architecture that imposes certain limitations on future network upgrades and scalability. To achieve flexible deployment of Network Private Network (NPN), we implemented the 5G core network architecture using Software Defined Networking (SDN) with Programming Protocol-Independent Packet Processors (P4) programmable switch. Subsequently, we conducted the connectivity test of the core network and analyzed the maximum achievable user capacity. Considering that the introduction of SDN may bring new security risks to private networks, we have designed a solution to mitigate SDN data plane Distributed Denial of Service (DDoS) attacks and have proven its effectiveness through practical experiments.

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Novel contour extraction algorithm for a moving target based on image fusion

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Guangdianzi Jiguang/Journal of Optoelectronics Laser 2005年第8期16卷 973-977页

作者： Zhao, Peng Cao, Jun Pu, Zhao-Bang Zhang, Tian-Wen Department of Automation Measurement and Control Harbin Institute of Technology Harbin 150001 China Mechanic and Electronic Institute Northeast Forestry University Harbin 150040 China Department of Computer Science and Engineering Harbin Institute of Technology Harbin 150001 China

A contour extraction algorithm for a moving target is proposed. This algorithm consists of three steps. Firstly, motion segmentation is applied respectively to infrared and visible image sequences to get an initial contour of a moving target. Secondly, a dynamic contour is applied to make the initial contour converge to the target's contour. Finally, two novel image fusions are applied. The first fusion minimizes L2 norm's square of the difference of control point vectors in two modal images without image registration. The second fusion is realized by the modified differential coupling with image registration. Contrasting detection experiments indicate the second fusion is better. Meanwhile, a fast iteration algorithm of dynamic contour based on the Newmark method is devised. A contrasting experiment indicates its iteration time for stable convergence decreases by 21.01% compared with the Wilson-θ method.

关键词： Object recognition

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Concept, Principle, and Modeling of Driving Risk Entropy Based on Human-Vehicle-Road Coupling Model for Autonomous Vehicle

SSRN

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SSRN 2024年

作者： Gao, Hongbo Yang, Hanqing Zhu, Juping Su, Huiping Wang, Ning Xie, Liping Li, Keqiang Department of Automation University of Science and Technology of China Hefei230026 China Institute of Advanced Technology University of Science and Technology of China Hefei230088 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Chongqing College of Mobile Communication Chongqing400044 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing100084 China

Driving risk entropy, based on entropy law, is an innovative concept proposed for intelligent driving systems. The concept deals with the driving risks caused by the human-vehicle-road system from the driving information obtained;however, driving risks are difficult to assess due to many influencing factors and great uncertainty. The risk entropy model of vehicles is visualized by introducing the concept of basic isotropic risk elliptic line (BIREL). Further incorporating the concept of information entropy, risk entropy models for vehicle interaction and vulnerable participants are established, and the risk entropy model for roads is developed using raster coordinates. Ultimately, a three-dimensional driving risk entropy model is constructed based on the human-vehicle-road coupling model, with appropriate weights assigned to each parameter through the DDPG algorithm. Experimental results demonstrate the effectiveness of the driving risk entropy model. © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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