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2023 China Automation Congress, CAC 2023

作者： Yao, Zhuobin Gan, Yahui Han, Zao Gao, Huan Li, Ang School of Automation Southeast University Key Laboratory of Measurement and Control of Systems of Engineering Ministry of Education NanJing China Intel Joint Research Institute on Intelligent Edge Computing Nanjing YingQi Intelligent Technology Co. Ltd. NanJing China

ISBN: (纸本)9798350303759

The deep crate grasping problem is a major challenge for manipulator in industrial applications. In order to solve the issue of deep crate grasping and ensure the path quality of the algorithm, this paper proposes a new hybrid obstacle avoidance planning algorithm based on goal-biased rapidly exploring random tree and improved artificial potential field (RRT-APF). Initially, the algorithm strategizes an efficient trajectory for the working element within the operational area. Subsequently, it dissects this trajectory through sampling, creating a sequence of sub-target points. These points serve as the basis for obstacle avoidance planning within the manipulator's configuration space, mitigating planning complexities. Moreover, the RRT algorithm is employed to address the challenge of local optima within the artificial potential field method. The stochastic nature of the RRT algorithm plays a crucial role in enabling the APF algorithm to break free from local optima. Ultimately, the efficacy of the algorithm is demonstrated through the planning of a path for obstacle avoidance on the DOBOT CR5 manipulator using MATLAB. © 2023 IEEE.

关键词： Trees (mathematics)

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Distributionally robust optimization based chance-constrained energy management for hybrid energy powered cellular networks

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Digital communications and Networks 2023年第3期9卷 797-808页

作者： Pengfei Du Hongjiang Lei Imran Shafique Ansari Jianbo Du Xiaoli Chu The Engineering Research Center of Intelligent Air-ground Integrated Vehicle and Traffic Control Ministry of EducationXihua UniversityChengdu610039China Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and TelecommunicationsChongqing400065China James Watt School of Engineering University of GlasgowGlasgowG128QQUK Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and TelecommunicationsXi'an710121China Electronic and Electrical Engineering University of SheffieldSheffieldS102TNUK

Energy harvesting has been recognized as a promising technique with which to effectively reduce carbon emis-sions and electricity expenses of base ***,renewable energy is inherently stochastic and inter-mittent,imposing formidable challenges on reliably satisfying users'time-varying wireless traffic *** addition,the probability distribution of the renewable energy or users’wireless traffic demand is not always fully known in *** this paper,we minimize the total energy cost of a hybrid-energy-powered cellular network by jointly optimizing the energy sharing among base stations,the battery charging and discharging rates,and the energy purchased from the grid under the constraint of a limited battery size at each base *** solving the formulated non-convex chance-constrained stochastic optimization problem,a new ambiguity set is built to characterize the uncertainties in the renewable energy and wireless traffic demands according to interval sets of the mean and *** this ambiguity set,the original optimization problem is transformed into a more tractable second-order cone programming problem by exploiting the distributionally robust optimization ***,a low-complexity distributionally robust chance-constrained energy management algo-rithm,which requires only interval sets of the mean and covariance of stochastic parameters,is *** results of extensive simulation are presented to demonstrate that the proposed algorithm outperforms existing methods in terms of the computational complexity,energy cost,and reliability.

关键词： Cellular networks Energy harvesting Energy management Chance-constrained Distributionally robust optimization

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Joint Power Allocation and Task Scheduling for Data Offloading in Non-Geostationary Orbit Satellite Networks

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IEEE Transactions on Network and Service Management 2025年第3期22卷 2882-2896页

作者： He, Lijun Jia, Ziye Wang, Juncheng Lansard, Erick Han, Zhu Yuen, Chau China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Xidian University State Key Laboratory of Integrated Services Networks Shaanxi Xi'an710071 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Nanjing211111 China Hong Kong Baptist University Department of Computer Science China Nanyang Technological University School of Electrical and Electronics Engineering 639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

In Non-Geostationary Orbit Satellite Networks (NGOSNs) with a large number of battery-carrying satellites, proper power allocation and task scheduling are crucial to improving data offloading efficiency. In this work, we jointly optimize power allocation and task scheduling to achieve energy-efficient data offloading in NGOSNs. Our goal is to properly balance the minimization of the total energy consumption and the maximization of the sum weights of tasks. Due to the tight coupling between power allocation and task scheduling, we first derive the optimal power allocation solution to the joint optimization problem with any given task scheduling policy. We then leverage the conflict graph model to transform the joint optimization problem into an Integer Linear Programming (ILP) problem with any given power allocation strategy. We explore the unique structure of the ILP problem to derive an efficient semidefinite relaxation-based solution. Finally, we utilize the genetic framework to combine the above special solutions as a two-layer solution for the original joint optimization problem. Simulation results demonstrate that our proposed solution can properly balance the reduction of total energy consumption and the improvement of the sum weights of tasks, thus achieving superior system performance over the current literature. © 2004-2012 IEEE.

关键词： Geostationary satellites

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Combined calibration method for large field of view multi-camera system

Combined calibration method for large field of view multi-ca...

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2022 Chinese Automation Congress, CAC 2022

作者： Sun, Wei Huo, Ju Li, You Xue, Muyao Zhou, JianBao Harbin Institute of Technology School of Electrical Engineering and Automation Harbin China Shanghai Space Propulsion Technology Research Institute Shanghai China Harbin Nuoxin University of Technology Measurement and Control Technology Co. Ltd. Harbin China

ISBN: (纸本)9781665465335

In the calibration process of multi-camera system with large field of vie23, aiming at the problem of self occlusion in the plane calibration method and the problem of low calibration accuracy of one-dimensional calibration methods, a calibration method of multi-camera system based on the combination of plane target and one-dimensional target is proposed. Firstly, a mathematical model of multi-camera calibration is established with pin-hole model and rigid body transformation theory;the internal parameters and distortion coefficients of each camera are calibrated by two-dimensional plane target;on this basis, analyze the uncertainty of imaging error of circular feature points, cost function of random sample consensus algorithm(RANSAC) is improved. Using the camera imaging model, the essential matrix between cameras is estimated, and the initial value of camera external parameters is decomposed and determined;lastly, multiple nonlinear optimization algorithms are used to refine and obtain the camera matrix, The simulation and actual experimental results show that the multi camera system combination calibration method proposed in this paper can realize the parameter calibration of four camera measurement system, and the measurement space is 2000mm×2000mm×2000mm, the 3D reconstruction error is less than 0.15mm. Compared with the traditional calibration method, it has more accurate calibration accuracy. © 2022 IEEE.

关键词： Calibration

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SE-COTR: A Novel Fruit Segmentation Model for Green Apples Application in Complex Orchard

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Plant Phenomics 2022年第1期4卷 12-25页

作者： Zhifen Wang Zhonghua Zhang Yuqi Lu Rong Luo Yi Niu Xinbo Yang Shaoxue Jing Chengzhi Ruan Yuanjie Zheng Weikuan Jia School of Information Science and Engineering Shandong Normal UniversityJinan 250358China State Key Laboratory of Biobased Materials and Green Papermaking Qilu University of Technology(Shandong Academy of Science)Jinan 25035China School of Informatics University of LeicesterLeicester LE17RHUK Department of Engineering Design and Mathematics University of the West of EnglandBristol BS161QYUK Fujian Key Laboratory of Intelligent Control and Manufacturing of Agricultural Machinery Wuyishan 354300China Key Laboratory of Facility Agriculture Measurement and Control Technology and Equipment of Machinery Industry Jiangsu UniversityZhenjiang 212013China

Because of the unstructured characteristics of natural orchards,the efficient detection and segmentation applications of green fruits remain an essential challenge for intelligent ***,an innovative fruit segmentation method based on deep learning,termed SE-COTR(segmentation based on coordinate transformer),is proposed to achieve accurate and real-time segmentation of green apples.

关键词： Application segmentation Complex

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A Two-Step Interval Estimation Method for State Monitoring of Port Intelligent Guided Vehicles with Unknown-but-Bounded Noises 8th

A Two-Step Interval Estimation Method for State Monitoring ...

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8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Jiang, Yuchen Lin, Yufeng Liang, ZhenLong Zhang, Yilian Key Laboratory of Transport Industry of Marine Technology and Control Engineering Shanghai Maritime University Shanghai201306 China College of Information and Communications Technology School of Engineering and Technology Central Queensland University Rockhampton4701 Australia

ISBN: (纸本)9789819602933

This paper investigates the problem of state monitoring of Intelligent Guided Vehicles (IGVs) operating in the complex port environment. Considering the perturbation suffered by the IGV, a two-step interval estimation method by integrating robust observer design with reachability analysis is proposed. First, we physically model the port IGV and its operating states subject to disturbances and noises, respectively. Then, a robust observer for the state monitoring of the considered IGV is designed and the existing conditions of the observer parameters are derived. In addition, based on the conditions for the existence of the proposed observer, the reachable set is obtained by the zonotope technique. Finally, the effectiveness of the proposed two-step interval estimation algorithm for the considered port IGV is verified by numerical simulations. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Automatic guided vehicles

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The control System of Intelligent Drug Delivery Car Based on Vision Guidance

The Control System of Intelligent Drug Delivery Car Based on...

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Artificial Intelligence technology (ACAIT), Asian Conference on

作者： Gang Wang Simin Ding Shufan Jing School of Mechanical Engineering Jilin Communications Polytechnic Changchun China School of Information and Control Engineering Jilin Institute of Chemical Technology Changchun China

ISBN: (数字)9798350359145

ISBN: (纸本)9798350359152

In response to the "contactless delivery" problem in hospitals, the control system of intelligent drug delivery car was designed based on vision guidance. The system takes raspberry pie as the control core and completes font recognition through high-definition camera; It determines the position and direction of the car through the OpenMV scanning marker line to complete the tracking and obstacle avoidance; It detects whether the drug is put down through the HX711 pressure sensor; It completes human-computer interaction through Bluetooth communication; It combines PID algorithm to realize closed loop control of speed, and controls the moving and changing direction of the car through DC motor module. The test results show that the system has high stability and good robustness, which has certain reference value for the intelligence of public medical service industry.

关键词： Pressure sensors Industries Drugs Epidemics Visualization Transportation control systems

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ViTGaze: Gaze Following with Interaction Features in Vision Transformers

arXiv

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arXiv 2024年

作者： Song, Yuehao Wang, Xinggang Yao, Jingfeng Liu, Wenyu Zhang, Jinglin Xu, Xiangmin School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan China School of Control Science and Engineering Shandong University Jinan China School of Future Technology South China University of Technology Guangzhou China

Gaze following aims to interpret human-scene interactions by predicting the person’s focal point of gaze. Prevailing approaches often adopt a two-stage framework, whereby multi-modality information is extracted in the initial stage for gaze target prediction. Consequently, the efficacy of these methods highly depends on the precision of the preceding modality extraction. Others use a single-modality approach with complex decoders, increasing network computational load. Inspired by the remarkable success of pre-trained plain vision transformers (ViTs), we introduce a novel single-modality gaze following framework called ViTGaze. In contrast to previous methods, it creates a novel gaze following framework based mainly on powerful encoders (relative decoder parameters less than 1%). Our principal insight is that the inter-token interactions within self-attention can be transferred to interactions between humans and scenes. Leveraging this presumption, we formulate a framework consisting of a 4D interaction encoder and a 2D spatial guidance module to extract human-scene interaction information from self-attention maps. Furthermore, our investigation reveals that ViT with self-supervised pre-training has an enhanced ability to extract correlation information. Many experiments have been conducted to demonstrate the performance of the proposed method. Our method achieves state-of-the-art (SOTA) performance among all single-modality methods (3.4% improvement in the area under curve (AUC) score, 5.1% improvement in the average precision (AP)) and very comparable performance against multi-modality methods with 59% number of parameters less. © 2024, CC BY-NC-SA.

关键词： Decoding

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Experimental Study on the Performance and Emission of Chinese Small Agricultural Diesel Engine Fuelled with Methanol/Biodiesel/DTBP

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Journal of Harbin Institute of technology(New Series) 2022年第3期29卷 67-78页

作者： Ruina Li Liang Zhang Jialong Zhu Yan Hua Zhong Wang School of Automotive and Traffic Engineering Jiangsu UniversityZhenjiang 212013JiangsuChina Vehicle Measurement Control and Safety Key Laboratory of Sichuan ProvinceChengdu 610039China Provincial Engineering Research Center for New Energy Vehicle Intelligent Control and Simulation Test Technology of Sichuan Chengdu 610039China

Diesel engine alternative fuels, such as methanol and biodiesel, are beneficial to reduce diesel engine emission. In order to study the influence of methanol and biodiesel on the performance, economy and emission of small agricultural diesel engine, the physical-chemical properties(cetane number, lower heat value(LHV), viscosity, etc.) of methanol and biodiesel were analyzed. The methanol and biodiesel showed good complementary property to some extent. When a large proportion of methanol was added into biodiesel, the cetane number of the methanol/biodiesel blend will be greatly reduced. Since the cetane number of the blend fuel has great influence on the combustion process of diesel engine, after testing for blending ratio of methanol/biodiesel, the blend was prepared with 5%(BM5), 10%(BM10) and 15%(BM15) methanol, respectively. Di-Tert-Butyl Peroxide(DTBP) was chosen as a cetane number improver to be added into methanol/biodiesel blend. 0.25%, 0.50% and 0.75% of DTBP was added into BM15. The bench test was carried out on a 186 FA diesel engine to study the effect of methanol and DTBP on the engine performance and emissions. The results show that, at rated condition, compared with biodiesel, the NO;concentration of BM5, BM10 and BM15 is reduced by 5.02%, 33.85% and 21.24%, and smoke is reduced by 5.56%, 22.22% and 55.56%. However, the engine power is also reduced by 5.77%, 14.23% and 25.41%, and the brake specific energy consumption is increased by 3.31%, 7.78% and 6.37%. The addition of DTBP in methanol/biodiesel could recover the engine power to the level of diesel. DTBP shows good effect on the reduction of the brake specific energy consumption and NO_(x), CO, HC concentration, but a little increase of exhaust smoke.

关键词： methanol biodiesel agricultural diesel engine combustion performance emission

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A Lightweight Object Detection Network for Industrial Robot Based YOLOv5

A Lightweight Object Detection Network for Industrial Robot ...

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2023 China Automation Congress, CAC 2023

作者： Zhong, Tao Gan, Yahui Han, Zao Gao, Huan Li, Ang School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Ministry of Education NanJing China Nanjing YingQi Intelligent Technology Co. Ltd. Intel Joint Research Institute on Intelligent Edge Computing NanJing China

ISBN: (纸本)9798350303759

With the rapid development of deep learning, it has been widely applied in fields such as computer vision, natural language processing, and robotics. Despite the superior performance of deep learning in object detection, most industrial vision robots still rely on traditional object detection methods due to computational constraints of robot controllers. In order to improve the performance of object detection for vision robots, a lightweight 3D object detection network based on You Only Look Once version 5 (YOLOv5) is proposed for satisfying industrial production. YOLOv5 work to efficiently object detection using deep convolutional networks. In terms of model deployment, we adopt a novel OpenVINO-based model deployment approach. The OpenVINO framework significantly enhances the inference speed of models by model optimization and compression. Our model achieves a 70% reduction in inference time compared to the baseline model on CPU. The effectiveness of the proposed method is demonstrated through experiments. © 2023 IEEE.

关键词： Object detection

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