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Global Multi-Object Transformer Tracking with Detecting and Attention Mechanism 13

Global Multi-Object Transformer Tracking with Detecting and ...

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13th ieee International Conference on CYBER Technology in automation, control, and Intelligent Systems, CYBER 2023

作者： Liu, Hengming Liu, Chang Hao, Zhicheng Zhou, Zhehai Qiu, Jun Institute of Applied Mathematics Beijing Information Science and Technology University Beijing China Beijing Information Science and Technology University Beijing Engineering Research Center of Optoelectronic Information and Instruments Beijing100192 China

ISBN: (纸本)9798350315196

Visual multiple-object tracking (MOT) has always been a research hotspot in the fields of computer vision and video image intelligence analysis. Tracking algorithms must not only accurately locate targets but also adapt to various types of interference while meeting robustness requirements. However, the uncertainty of the number of objects in the scene, mutual occlusion between objects, and the low discriminability of object features have led to slow progress in the practical application of visual multiple-object tracking. To address this issue, we designed a modified attention mechanism module and embedded it into a transformer-based global multiple-object tracking architecture, generating global trajectories for all objects. This forms the proposed efficient algorithm for object tracking. For larger convolution kernels, our method effectively extracts each feature in the receptive field while reducing computation costs, thus improving algorithm efficiency. We conducted the experiments on MOT17 and TAO, and achieved the state-of-the-art results. Experimental results show that our proposed method outperforms existing models overall, ensuring stable object trajectories while maintaining high-quality detection. © 2023 ieee.

关键词： computational efficiency

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Validation of a two-wheel vehicle model using Genetic Algorithm

Validation of a two-wheel vehicle model using Genetic Algori...

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International symposium on computational intelligence and Informatics

作者： Attila Widner Balázs Varga Dániel Medgyesi Tamás Tettamanti Dept. of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Fac. of Transportation Engineering and Vehicle Engineering Budapest Hungary Dept. of Innovative Vehicles and Materials John von Neumann University GAMF Fac. of Engineering and Computer Science Kecskemét Hungary

ISBN: (纸本)9798350398830

Vehicle dynamics simulation is widely used in the automotive industry. The usability of each model depends on how well it can replicate the behaviour of the real vehicle. Each simulation model must go through a thorough investigation process- model validation- before use. Accordingly, the research introduces a comprehensive methodological framework for vehicle dynamics model validation using a sophisticated vehicle dynamics measurement system and a machine learning algorithm. The validation process of a two-wheel vehicle model (bicycle model) is presented where the authors’ previously proposed work is exploited as a base and further developed, i.e. by using a Genetic Algorithm (GA) the vehicle parameters (yaw inertia, axle cornering stiffness) are estimated in an automatized fashion.

关键词： Industries Computer science Mechatronics Machine learning algorithms computational modeling Vehicle dynamics Usability

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Determining traffic node reliability by fuzzy fault tree analysis and small scaled model

Determining traffic node reliability by fuzzy fault tree ana...

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International symposium on computational intelligence and Informatics

作者： Ilona Tompa Péter Bakucz Kiss Gábor Bánki Donát Faculty of Mechanical and Safety Engineering Óbuda University Budapest Hungary

ISBN: (纸本)9798350398830

In this paper, we outline the analysis of a traffic node’s safety using a fuzzy fault tree method and a small-scaled model to gain information on the reliability of the node. The reliability of the dynamics of the node is determined by using the fuzzy FTA optimized minimal cut set procedure in a planned, small-scaled real environment, which requires testing the procedure in real-time and in an embedded environment. The optimization is based on percolation theory.

关键词： Analytical models Heuristic algorithms computational modeling Reliability theory Sensor systems Real-time systems Safety

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Multi-target Tracking with Random Finite Set in Decentralized Large-scale Sensor Networks

Multi-target Tracking with Random Finite Set in Decentralize...

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2022 ieee International Conference on Unmanned Systems, ICUS 2022

作者： Su, Lingfei Dong, Xiwang Hua, Yongzhao Yu, Jianglong Ren, Zhang School of Automation Science and Electrical Engineering Beihang University Science and Technology On Aircraft Control Laboratory Beijing China Institute of Artificial Intelligence Beihang University Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

This paper presents the multi-target tracking (MTT) problem in decentralized large-scale sensor networks. A novel random finite set (RFS)-based framework is designed, including an improved Probability Hypothesis Density filter with Gaussian Mixture (GM-PHD) representation, and an improved Generalized Covariance Intersection (GCI) fusion algorithm. For the local GM-PHD filter, the intensity of new-born targets is initialized by pre-segmenting the measurement set to address the uncertainty of measurement origin and the computational burden of large-scale measurements. Then, a sensor node-dependent clutter model is established to deal with the cardinality overestimation problem brought by the decentralized structure. For the proposed fusion algorithm, i.e., fusing the posterior PHDs generated by the proposed GM-PHD filters in a distributed manner, it is based on the idea of compensating the severe missed detection problem of GCI in the case of large-scale fusing resources by arithmetic average (AA) fusion. In this way, GCI and AA can be fully utilized to guarantee the estimation accuracy for common targets and, respectively, the robustness for exclusive targets. A simulation of a decentralized large-scale network demonstrates the effectiveness of the proposed framework with respect to estimation accuracy and computational cost. © 2022 ieee.

关键词： Sensor nodes

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Evaluation of the Use of an Intelligent System in the Calibration of a Refined Car-Following Model

Evaluation of the Use of an Intelligent System in the Calibr...

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International symposium on computational intelligence and Informatics

作者： Mădălin-Dorin Pop Octavian Proştean Mihai V. Micea Computer and Information Technology Department Politehnica University of Timișoara Timișoara România Automation and Applied Informatics Department Politehnica University of Timișoara Timișoara România

ISBN: (纸本)9798350398830

This paper aims to extract the computational logic of a hybrid method for online calibration of car-following models and apply it to a refined car-following model that incorporates the behavior of vehicles moving on the adjacent traffic lanes. This calibration method combines the concept of Kalman filters with the Takag-Sugeno Fuzzy Inference System (T-S FIS). Furthermore, this paper analyzes the influence of the lane change behavior on the calibration process. The testing of the hybrid calibration method in the case of a refined car-following model uses real traffic data and it is followed by a discussion of the results based on day/night traffic behaviors.

关键词： computational modeling Data models Real-time systems Calibration Behavioral sciences Delays Kalman filters

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A Blockchain-based Dynamic Support of Kinematic Testing

A Blockchain-based Dynamic Support of Kinematic Testing

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International symposium on computational intelligence and Informatics

作者： Bence Tureczki Henriette Steiner–Komoróczki Katalin Szenes Doctoral School of Applied Informatics and Applied Mathematics Óbuda University Budapest Hungary Institute for Cyber-physical Systems John von Neumann Faculty of Informatics Óbuda University Budapest Hungary

ISBN: (纸本)9798350398830

This article presents a blockchain-supported evaluation and publishing method for kinematic models. As a modeling tool, OpenSim was chosen. The blockchain facilitates the hiding of the private part of the model, preserving the authors’ rights, and, at the same time, the publication of that part to be evaluated. For this evaluation, such excellence criteria are offered that were originally created for supporting corporate activities. The secret part of the model is tokenized by Ethereum-based NFTs (Non-Fungible Tokens). These tokens will provide for copyright issues.

关键词： Computer science Mechatronics Publishing computational modeling Kinematics Nonfungible tokens Informatics

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A Multimedia Framework for Continuum Robots: Systematic, computational, and control Perspectives

A Multimedia Framework for Continuum Robots: Systematic, Com...

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ieee International symposium on Intelligent Signal Processing and Communication Systems (ISPACS)

作者： Po-Yu Hsieh June-Hao Hou Graduate Institute of Architecture National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9798350389210

ISBN: (纸本)9798350389227

Continuum robots, which often rely on interdisciplinary and multimedia collaborations, have been increasingly recognized for their potential to revolutionize the field of humancomputer interaction (HCI) in varied applications due to their adaptive, responsive, and flexible characteristics. Despite their promises, the lack of an integrated framework poses a significant limitation for both users and developers, resulting in inefficiency and complexity during preliminary developments. Thus, this paper introduces a unified framework for continuum robotic systems that addresses these challenges by integrating system architecture, dynamics computation, and control strategy within a computer-aided design (CAD) platform. The proposed method allows for efficient modeling and quick preview of the robot performance, and thus facilitating iterative design and implementation, with a view to enhancing the quality of robot developments.

关键词： Solid modeling Visualization Systematics Design automation computational modeling Heuristic algorithms Predictive models computational efficiency Continuum robots Iterative methods

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Improvements to Speed and Efficacy in Non-Stationary Learning in a Flapping-Wing Air Vehicle: Constrained and Unconstrained Flight

Improvements to Speed and Efficacy in Non-Stationary Learnin...

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ieee symposium Series on computational intelligence (ieee SSCI)

作者： Gallagher, John C. Sam, Monica Univ Cincinatti Dept Elect Engn & Comp Sci Cincinnati OH 45221 USA Wright State Univ Dept Comp Sci & Engn Dayton OH 45435 USA

ISBN: (纸本)9781728190488

Small Flapping-Wing Micro-Air Vehicles (FW-MAVs) may experience wing damage and wear while in service with even small amounts introducing significant deficits in maintaining path control. Previous work employed a custom Evolutionary Algorithm (EA) that adapted wing motion patterns, while in flight and in normal online service, to compensate for wing damage. Although generally successful in finding solutions to this challenging online non-stationary problem, the previous methods would very often require hours of flight time to reach full success and sometime failed altogether in cases of extreme wing damage. This paper details a new approach that reduces the required learning time by an order of magnitude and extends the range of damage over which one can expect suitable performance. A discussion of what changes were made and why they were made will be provided along with extensive simulation results demonstrating the claims of success. The paper will also provide discussion of what additional work is possible now that both speed and efficacy have been sufficiently improved to support practical in-flight learning in real vehicles.

关键词： Flapping-Wing Micro Air Vehicle Evolvable and Adaptive Hardware Evolutionary Computation Adaptive control

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Evaluating of IAQ-index and TVOC As Measurements Parameters for IoT-based Hazardous Gases Detection and Alarming Systems 20

Evaluating of IAQ-index and TVOC As Measurements Parameters ...

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20th ieee Jubilee World symposium on Applied Machine intelligence and Informatics, SAMI 2022

作者： Al-Okby, Mohammed Faeik Ruzaij Neubert, Sebastian Roddelkopf, Thomas Fleischer, Heidi Thurow, Kerstin Technical Institute of Babylon Kufa Iraq Rostock18119 Germany Leibniz Institute for Baltic Sea Research Warnemünde Rostock18119 Germany University of Rostock Institute of Automation Rostock18119 Germany

ISBN: (纸本)9781665497046

Hazardous gases detection and alarming systems required prior gas sensors testing for selecting the optimal sensors before system design and implementation. Several parameters can be measured by commercially available gas sensors such as indoor air quality index (IAQ-index), equivalent CO2, equivalent Ethanol, equivalent H2, total volatile organic compounds (TVOC), and so on. In this paper, we test two novel metal oxide semiconductor (MOX) gas sensors for measuring IAQ-index, and TVOC which are the SGP30, and SGP40. The gas sensors have been combined with a low-cost IoT-based microcontroller as a sensor node. The sensor node implements several tasks such as data acquisition, filtering, and transmitting to an IoT-cloud for monitoring, processing, and storing. The sensor node has been tested with several VOC to measure the IAQ-index and TVOC in parallel. The tests used a fixed volume (5μL) for all the selected VOC materials and the tests implemented from different distances (25cm, 40cm, and 100cm) between the sensors and the VOC spilling source to check the performance of the sensors regarding the used volume and distances from the leakage source. © 2022 ieee.

关键词： Volatile organic compounds Semiconductor device measurement Gases Ethanol Sensor systems Sensors Task analysis

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A dipole model-based approach for magnetic disturbance compensation of mobile robots using magnetometer arrays

A dipole model-based approach for magnetic disturbance compe...

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International symposium on computational intelligence and Informatics

作者： Massimo Stefanoni Ákos Odry Peter Sarcevic Doctoral School of Applied Informatics and Applied Mathematics Óbuda University Budapest Hungary Department of Mechatronics and Automation University of Szeged Szeged Hungary

Magnetic sensors are used for localization purposes in both outdoor and indoor applications. In indoor applications, three-axis magnetometers cannot be used as compasses due to the presence of hard and soft-iron effects that require to be neglected. This paper proposes a new method for magnetic compensation for an unknown metallic object. It considers the source of the disturbance as a dipole, uses an array of four no-coplanar magnetometers, and exploits an Artificial Neural Network (ANN). The ANN receives as inputs the measurement differences of each pairwise sensor and provides as output the disturbance components related to one sensor of the array. In such a way, by estimating the magnetic disturbances, it is possible to evaluate the real value of the Earth’s magnetic field. The ANN is trained by exploiting a database generated by using the dipole model and by evaluating the model for different intensities and orientations. The simulation results show how the method can effectively reduce the introduced disturbances in the surroundings of the object with a Mean Absolute Error (MAE) in the order of $0.3 \mu \mathrm{T}$, and a maximum error in the range from $1.8767 \mu \mathrm{T}$ to $2.5252 \mu \mathrm{T}$. The proposed method contributes to the development of improved localization algorithms, where the proposed disturbance rejection technique enables the utilization of reliable measurements for mobile robot pose estimation.

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