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7th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2024

作者： Zhang, Jian Wu, Sheng Liu, Wenwei Feng, Hui Hu, Bo School of Information Science and Technology Fudan University Shanghai200433 China Shanghai Institute of Intelligent Electronics & Systems Shanghai200433 China

ISBN: (纸本)9798350350890

The event cameras generate asynchronous event sequences, rendering most existing image-based algorithms in-applicable for direct use and processing. Therefore, the development of a simulator that utilizes event streams captured by an event camera as input and reconstructs image sequences as output is crucial for subsequent tasks such as high-speed moving object tracking, object recognition and detection, and SLAM. Despite the extensive research and attention garnered by deep learning-based image sequence generation, there remains a problem of local representation information loss during the reconstruction process from event streams to image sequences. Existing solutions, whether based on Stacking Based on Time (SBT) or Stacking Based on Events (SBE), exhibit significant limitations when using a single stacking approach. To address the insufficiency in feature representation capability, this paper proposes a visual image conversion method based on multi-view feature fusion, effectively transforming event streams into traditional image sequences. Extensive experiments and dataset validations, utilizing multiple evaluation metrics including both global and local assessments, demonstrate the advantages of our proposed method. © 2024 IEEE.

关键词： Image reconstruction

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Design of a Small-Scale Locust-Inspired Robot Capable of Jump-gliding Locomotion

Design of a Small-Scale Locust-Inspired Robot Capable of Jum...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Zhang, Weitao Wei, Zisen Xu, Yi Peng, Liang Dong, Changwen Jin, Yanzhou Shi, Qing Ministry of Education Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Intelligent Robotics Institute School of Mechatronical Engineering Beijing100081 China

ISBN: (纸本)9798350325706

Small-scale robots are widely used in real-world rescue missions, but their mobility and movement range are still limited. One solution to improve their adaptability to complex environments is to introduce jumping and gliding strategies into the robot design. In this paper, we developed a small-scale locust-inspired robot capable of active (propeller-driven) gliding after launching from the ground, which had a body length of 19.1 cm and a weight of 97 g. On the basis of the locust's musculoskeletal model, the jumping system was designed by a six-bar mechanism which can amplify the power. To improve the lift in gliding phase while reducing the draft in jumping phase, the gliding system with a folding wing and a front propeller was proposed corresponding to the fixed-wing principle. The results obtained through a series of experimental tests reveal that the robot achieves a jumping height of 0.15 m and a passive gliding distance of 1.5 m, which has a glide ratio of 1.13. Remarkably, actuating by a propeller, the robot can jump up to a height of 0.20 m, covering a gliding distance of 2.9 m. It is worth noting that the glide ratio of the robot improves by 91.2% in the propeller-driven jump-gliding mode. © 2023 IEEE.

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Event-based Fast Visual-Inertial Odometry by Adaptive Slicing of Time Surface 7

Event-based Fast Visual-Inertial Odometry by Adaptive Slicin...

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7th IEEE Advanced information technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Lu, Jun Feng, Hui Liu, Wenwei Hu, Bo Fudan University School of Information Science and Technology Shanghai200433 China Shanghai Institute of Intelligent Electronics & Systems Shanghai200433 China

ISBN: (纸本)9798350339161

Event cameras are asynchronous bio-inspired vision sensors, possessing advantages such as high output frequency and high dynamic range, enabling the output of valid information in challenging scenes. Current visual odometry (VO) pipelines based on event cameras primarily leverage the high dynamic range advantage of event cameras, but struggle to achieve a balance between system accuracy and output frequency. In this paper, we propose a fast visual-inertial odometry (VIO) pipeline with adaptive slicing of the Time Surface, leveraging the complementary advantages of event cameras and standard cameras to achieve accurate and fast motion estimator. To achieve this goal, we introduce the method of valid events adaptive slice and an asynchronous tightly-coupled strategy during the optimization phase between standard cameras and event cameras/IMU. Experimental results on public benchmark datasets demonstrate that our pipeline outperforms state-of-the-art event-based VIO pipelines in terms of both accuracy and speed. © 2024 IEEE.

关键词： Pipelines

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Backstepping-based adaptive control of indoor miniature airship 8

Backstepping-based adaptive control of indoor miniature airs...

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8th International Conference on Control, robotics and Cybernetics, CRC 2023

作者： Li, Hongming Fang, Yongchun Dong, Jinyang Yu, Hai Nankai University Institute of Robotics and Automatic Information Systems College of Artificial Intelligence Tianjin China Shenzhen Research Institute of Nankai University Institute of Intelligence Technology and Robotic Systems Shenzhen China

ISBN: (纸本)9798350330588

Recently, research on the flight control of indoor small unmanned airships has attracted much attention. Unmanned airship has characteristics of low manufacturing cost, long dwell time, low energy consumption and so on. Under the premise of ignoring the external wind interference, a controller is designed that makes the airship move to the preset point and stay in the air. The mathematical model of the unmanned airship is first introduced in this paper. A six-degree-of-freedom equation of motion is established after force analysis, and then it is simplified to a three-degree-of-freedom model according to the geometric symmetry of the airship. Subsequently, the motion process of the airship is disassembled into horizontal motion and vertical motion, the backstepping method is used to design the controller, and unknown parameters in the model are processed with adaptive control. Finally, computer simulation experiments are carried out to verify the correctness of the model and the effectiveness of the controller from a mathematical point of view. In this paper, a small unmanned airship motion control system is designed, and its feasibility from the perspective of computer simulation is verified. These studies provide initial exploratory work on control methods for indoor unmanned airships. © 2024 IEEE.

关键词： Degrees of freedom (mechanics)

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MATD3-Based End-Edge Collaborative Resource Optimization for NOMA-Assisted Industrial Wireless Networks

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Computers, Materials & Continua 2025年第2期82卷 3203-3222页

作者： Ru Hao Chi Xu Jing Liu College of Information Engineering Shenyang University of Chemical TechnologyShenyang110142China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang110016China

Non-orthogonal multiple access (NOMA) technology has recently been widely integrated into multi-access edge computing (MEC) to support task offloading in industrial wireless networks (IWNs) with limited radio resources. This paper minimizes the system overhead regarding task processing delay and energy consumption for the IWN with hybrid NOMA and orthogonal multiple access (OMA) schemes. Specifically, we formulate the system overhead minimization (SOM) problem by considering the limited computation and communication resources and NOMA efficiency. To solve the complex mixed-integer nonconvex problem, we combine the multi-agent twin delayed deep deterministic policy gradient (MATD3) and convex optimization, namely MATD3-CO, for iterative optimization. Specifically, we first decouple SOM into two sub-problems, i.e., joint sub-channel allocation and task offloading sub-problem, and computation resource allocation sub-problem. Then, we propose MATD3 to optimize the sub-channel allocation and task offloading ratio, and employ the convex optimization to allocate the computation resource with a closed-form expression derived by the Karush-Kuhn-Tucker (KKT) conditions. The solution is obtained by iteratively solving these two sub-problems. The experimental results indicate that the MATD3-CO scheme, when compared to the benchmark schemes, significantly decreases system overhead with respect to both delay and energy consumption.

关键词： Industrial wireless networks(IWNs) multi-access edge computing(MEC) non-orthogonal multiple access(NOMA) task offloading resource allocation

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DNN Based Geoid Undulation Prediction Accuracy Evaluation Using EGM08 Gravity Model

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Transactions of the Korean institute of Electrical Engineers 2022年第8期71卷 1153-1163页

作者： Kim, Hyun-Seok Park, Chan-Sik Dept. of Intelligent Systems & Robotics Research Institute for Computer and Information Communication Chungbuk National University Korea Republic of Agency for Defense Development Korea Republic of

The difference between mean sea level and ellipsoid height is defined as geoid relief, which is essential information when building barometric altimeter/GPS combined systems or terrain matching systems. Therefore, an accurate calculation of the geoid undulation is required. In this paper, we propose a deep neural network method for calculating geoid undulations in real time in an embedded system. Then, using the EGM08 geoid model of order 2160, training data at intervals of 0.001 degrees were generated, and the prediction model accuracy was evaluated for 4 cases according to the number of hidden layers. As the number of hidden layers increased, the prediction accuracy increased, and it was confirmed that the calculation time also increased proportionally. © 2022 Korean institute of Electrical Engineers. All rights reserved.

关键词： Forecasting

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Variable-order fractional derivative rutting depth prediction of asphalt pavement based on the RIOHTrack full-scale track

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Science China(information Sciences) 2023年第5期66卷 196-214页

作者： Yu WANG Jiaojiao YAN Wei HUANG Leszek RUTKOWSKI Jinde CAO School of Mathematics Southeast University Jiangsu Provincial Key Laboratory of Networked Collective Intelligence Southeast University Intelligent Transportation System Research Center Southeast University Systems Research Institute of the Polish Academy of Sciences Institute of Computer Science AGH University of Science and Technology Information Technology Institute University of Social Sciences Yonsei Frontier Lab Yonsei University

Rutting deformation is typical damage to asphalt pavement and can be quantitatively described as the time-varying mechanical deformation feature of the asphalt mixture during the creep process. First,a nonlinear viscoelastic creep model is established based on the Caputo variable-order fractional *** fractional order in this model is not fixed and is defined as a time-varying function. The time-dependent mechanical properties of asphalt mixtures are efectively reflected. Based on the modified Burgers model, the variable-order function is revised to a linear form. Second, the variable-order fractional Burgers rutting model is obtained by fitting the test data of the RIOHTrack full-scale track. The Levenberg-Marquardt optimization algorithm is used to analyze the test data and the corresponding parameters to obtain more accurate and applicable variable-order fractional rutting mechanics and empirical models for diferent asphalt pavement structures. Finally, according to the classification of the pavement structure, structures III and VI are taken as examples. The rutting prediction and comparison results of several representative pavement structures are obtained to verify that the proposed rutting prediction model can also accurately predict all road sections of RIOHTrack. The new model is also compared with the rutting model of the mechanistic-empirical pavement design guide, the fractional-order Burgers rutting model, and the modified Burgers rutting model. The fitting results are evaluated using the determination coefficient R2. The results show that the variable-order fractional Burgers rutting model proposed in this study exhibits a better fit and is more applicable to describe the rutting deformation of asphalt pavement.

关键词： RIOHTrack full-scale track Caputo fractional derivative variable-order fractional modified Burgers model rutting prediction

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Auto-focusing method for wide-spectral-illumination lens-Free imaging 14

Auto-focusing method for wide-spectral-illumination lens-Fre...

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Holography, Diffractive Optics, and Applications XIV 2024

作者： Zhang, Jialin Yang, Ying Wang, Zhenguo Research Center for Intelligent Information Technology Nantong University No. 9 Seyuan Road Jiangsu Province Nantong China Information and Systems Engineering Fukuoka Institute of Technology Fukuoka Japan

ISBN: (纸本)9781510682085

Auto-focusing plays a crucial role in lens-free holographic microscopy. In this research, we propose a new axialdifference- based Robert method aimed at improving the accuracy of distance estimation under wide-spectral illumination. By establishing connections between intensity derivation, spectral distribution changes, and object distribution, we develop a robust method. The procedure involves image acquisition, preprocessing, axial difference computation, and sharpness-based distance determination. Both simulations and experiments verify the method's ability to enhance auto-focusing accuracy in wide-spectral illumination scenarios. To demonstrate its broad applicability, experiments are carried out using ultra-wide-spectral illumination on various samples, including a resolution target and a Tilia stem cross-section. © 2024 SPIE. All rights reserved.

关键词： Holography

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HOI-Based Method for Detecting Cell Phone Behavior in Industrial Safety Production Environments 4

HOI-Based Method for Detecting Cell Phone Behavior in Indust...

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4th International Conference on Computer Science, Electronic information Engineering and intelligent Control technology, CEI 2024

作者： Nong, Zijian Shi, Shaofei Jiang, Chi Zhang, Ke Zhang, Yin Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Guangdong Intelligent Robotics Institute Dongguan China

ISBN: (纸本)9798350378542

To address the practical problems of algorithm inference timeliness and the complex environment in industrial settings, The presented dissertation introduces a comprehensive human-object interaction recognition technique, leveraging the attention-based architecture of the Transformer model. By sampling key features at different scales from the industrial complex environment and using Transformer's attention mechanism to aggregate global information, the algorithm achieves accurate detection of targets in complex environments while eliminating post-processing processes such as non-maximal value suppression to achieve real-time detection. Moreover, a deformable attention module is used to optimize small target detection and the multi-headed attention mechanism of Transformer, which adaptively adjusts the position and shape of the feature extraction window, reducing the computational effort of the attention computation process and accelerating the model training time. The investigation outcomes reveal that the introduced HOI-centric technique for identifying mobile phone infractions within industrial safety contexts exhibits superior accuracy in detection and notable enhancements in computational efficiency when benchmarked against other sophisticated algorithms in the expanded mobile phone category within the HICO-DET dataset. © 2024 IEEE.

关键词： Object detection

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intelligent upper-limb exoskeleton integrated with soft bioelectronics and deep learning for intention-driven augmentation

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npj Flexible Electronics 2024年第1期8卷 856-868页

作者： Jinwoo Lee Kangkyu Kwon Ira Soltis Jared Matthews Yoon Jae Lee Hojoong Kim Lissette Romero Nathan Zavanelli Youngjin Kwon Shinjae Kwon Jimin Lee Yewon Na Sung Hoon Lee Ki Jun Yu Minoru Shinohara Frank L.Hammond Woon-Hong Yeo Department of Mechanical Roboticsand Energy EngineeringDongguk UniversitySeoul 04620Republic of Korea IEN Center for Wearable Intelligent Systems and Healthcare Institute for Electronics and NanotechnologyGeorgia Institute of TechnologyAtlantaGA 30332USA School of Electrical and Computer Engineering Georgia Institute of TechnologyAtlantaGA 30332USA George W.Woodruff School of Mechanical Engineering Georgia Institute of TechnologyAtlantaGA 30332USA School of Industrial Design Georgia Institute of TechnologyAtlantaGA 30332USA School of Electrical and Electronic Engineering Yonsei UniversitySeoul 03722Republic of Korea School of Biological Sciences Georgia Institute of TechnologyAtlantaGA 30332USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory University School of MedicineAtlantaGA 30332USA Institute for Materials Parker H.Petit Institute for Bioengineering and BiosciencesInstitute for Robotics and Intelligent MachinesGeorgia Institute of TechnologyAtlantaGA 30332USA

The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper ***,we introduce an intelligent upper-limb exoskeleton system that utilizes deep learning to predict human intention for strength *** embedded soft wearable sensors provide sensory feedback by collecting real-time muscle activities,which are simultaneously computed to determine the user’s intended *** deep learning predicts four upper-limb joint motions with an average accuracy of 96.2%at a 500–550 ms response rate,suggesting that the exoskeleton operates just by human *** addition,an array of soft pneumatics assists the intended movements by providing 897 newtons of force while generating a displacement of 87mm at *** intent-driven exoskeleton can reduce human muscle activities by 3.7 times on average compared to the unassisted exoskeleton.

关键词： skeleton learning utilize

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