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A Real-Time, Robust, and Versatile Visual-SLAM Framework Based on Deep Learning Networks

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Zhang, Xiao Dong, Hongbin Zhang, Haoxin Zhu, Xiaozhou Li, Shuaixin Deng, Baosong Harbin Engineering University College of Computer Science and Technology National Engineering Laboratory for E-Government Modeling and Simulation Harbin150009 China Defense Innovation Institute Chinese Academy of Military Science Beijing100850 China Sun Yat-sen University College of Systems Science and Engineering Guangzhou510275 China Intelligent Game and Decision Laboratory Beijing100166 China

In this article, we investigate the paradigm of deep learning techniques to enhance the performance of visual-based simultaneous localization and mapping (vSLAM) systems, particularly in challenging environments. By leveraging deep feature extraction and matching methods, we propose a robust, versatile hybrid visual SLAM framework, Rover-SLAM, aimed at improving adaptability in adverse conditions, such as dynamic lighting conditions, areas with weak textures, and camera jitter. Building on excellent learning-based algorithms of recent years, we designed from scratch a novel system that uses the same feature extraction and matching approaches for all SLAM tasks. Our system supports multiple modes, including monocular, stereo, monocular-inertial, and stereo-inertial configurations, offering flexibility to address diverse real-world scenarios. Through comprehensive experiments conducted on publicly available datasets and self-collected data, we demonstrate the superior performance of our Rover-SLAM system compared to the state-of-the-art (SOTA) approaches. We also conducted an in-depth analysis of the integration of visual SLAM with deep learning methods quantitatively to provide insights for future research endeavors in this domain. The experimental results showcase the system's capability of achieving higher localization accuracy and robust tracking performance. © 1963-2012 IEEE.

关键词： Stereocenters

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Enhancing realism in LiDAR scene generation with CSPA-DFN and linear cross-attention via Diffusion Transformer model

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Neural Networks 2025年 189卷 107503页

作者： Ye, Shaoxun Di, Xiaoguang Liao, Ming Li, Ximing Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin150080 China

Point cloud diffusion models have found extensive applications in autonomous driving and robotics. However, there is still a big gap between their generated LiDAR scene samples and real-world data in terms of visual quality. This discrepancy primarily arises from the loss of detailed information during the decoding process from latent space and the lack of guidance from global 3D structural information in the point cloud generation process, leading to distortions and artifacts in LiDAR scene samples. In this paper, we propose a novel LiDAR Diffusion Transformer Model that integrates Channel-Spatial Parallel Attention and Dilation Fusion Network (CSPA-DFN) with a linear cross-attention post-processing module to refine the generated LiDAR scene samples. Specifically, CSPA-DFN is designed to simultaneously emphasize detailed features across different channels and spatial locations in parallel, leveraging multi-scale dilated convolutions and channel grouping to preserve and enhance these detailed features. In order to provide global 3D structural information and balance performance and efficiency, we design a post-processing module that fuses voxelized features and range images using a linear ReLU cross-attention mechanism. Our approach is evaluated on the unconditional generation task using the KITTI-360 and nuScenes datasets, achieving the state-of-the-art results in LiDAR scene's generation quality. Furthermore, by incorporating semantic labels and camera views into the latent space, in addition to enhancing the model's semantic understanding capability for LiDAR scenes, our method also demonstrates additional performance improvements compared to previous works in terms of LiDAR scene's visual quality. The code implementation has been released on https://***/HITysx/LiDAR-Scene-Generation. © 2025 Elsevier Ltd

关键词： Photointerpretation

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Prophet: Prompting Large Language Models with Complementary Answer Heuristics for Knowledge-based Visual Question Answering

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年

作者： Yu, Zhou Ouyang, Xuecheng Shao, Zhenwei Wang, Meng Yu, Jun Hangzhou Dianzi University School of Computer Science Key Laboratory of Complex Systems Modeling and Simulation China Hangzhou Dianzi University HDU-ITMO Joint Institute China Hefei University of Technology School of Computer Science and Information Engineering China Department of Computer Science and Technology Harbin Institute of Technology Shenzhen China

Knowledge-based visual question answering (VQA) requires external knowledge beyond the image to answer the question. Early studies retrieve required knowledge from explicit knowledge bases (KBs), which often introduces irrelevant information to the question, hence restricting the performance of their models. Recent works have resorted to using a powerful large language model (LLM) as an implicit knowledge engine to acquire the necessary knowledge for answering. Despite the encouraging results achieved by these methods, we argue that they have not fully activated the capacity of the blind LLM as the provided textual input is insufficient to depict the required visual information to answer the question. In this paper, we present Prophet—a conceptually simple, flexible, and general framework designed to prompt LLM with answer heuristics for knowledge-based VQA. Specifically, we first train a vanilla VQA model on a specific knowledge-based VQA dataset without external knowledge. After that, we extract two types of complementary answer heuristics from the VQA model: answer candidates and answer-aware examples. The two types of answer heuristics are jointly encoded into a formatted prompt to facilitate the LLM's understanding of both the image and question, thus generating a more accurate answer. By incorporating the state-of-the-art LLM GPT-3 [1], Prophet significantly outperforms existing state-of-the-art methods on four challenging knowledge-based VQA datasets. Prophet is general that can be instantiated with the combinations of different VQA models (i.e., both discriminative and generative ones) and different LLMs (i.e., both commercial and open-source ones). Moreover, Prophet can also be integrated with modern large multimodal models in different stages, which is named Prophet++, to further improve the capabilities on knowledge-based VQA tasks. © 1979-2012 IEEE.

关键词： Question answering

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Evolutionary neural architecture search for automatically designing CNN-GRU-Attention neural networks for turntable servo systems

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Expert systems with Applications 2025年 283卷

作者： Xie, Cheng Xue, Bing Yang, Mingyi Zhang, Mengjie Xu, Zhigang Wang, Junyi Chen, Songlin Liu, Yang Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang110169 China Centre for Data Science and Artificial Intelligence & School of Engineering and Computer Science Victoria University of Wellington Wellington6140 New Zealand University of Chinese Academy of Sciences Beijing101408 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin Institute of Technology Heilongjiang Harbin150001 China

Turntable servo systems are important experimental devices utilized in the semi-physical simulation and testing of aircraft. Building a model for turntable servo systems, which can accurately predict their operating states or behaviors, is important for the development and debugging of the whole servo control system. However, servo systems usually have complex nonlinear characteristics and external disturbances, which brings challenges to the accurate modeling of them. Therefore, this paper develops a modeling method for turntable servo systems by using CNN-GRU-Attention hybrid neural network models. The CNN-GRU-Attention model is used for compensating the nonlinear terms of the known dynamics model, thus effectively improving the modeling accuracy. Considering the complex architectures of the above hybrid model, an evolutionary neural architecture search (ENAS) algorithm is proposed accordingly, which can automatically design the architecture of the CNN-GRU-Attention models. During the designing process, a variable-length encoding strategy is proposed to represent the possible architectures, and novel crossover and mutation operators are proposed accordingly for the evolution of individuals. In addition, the real-time constraints are considered in the design of the search space, so that all the searched models can meet the real-time requirements. The experimental results show the CNN-GRU-Attention models obtained by the proposed ENAS algorithm achieve superior prediction performance over the peer competitors in most tasks. The effectiveness of the proposed method is further verified by analyzing the convergence and the search results. © 2025

关键词： Synchros

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Integrated Cellular Framework for modeling Ecosystems: Theory and Applications (vol 94, 213, 2017)

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simulation-TRANSACTIONS OF THE SOCIETY FOR modeling AND simulation INTERNATIONAL 2018年第9期94卷 NP1-NP1页

作者： Kazi, Baha Uddin Wainer, Gabriel Department of Systems and Computer Engineering Center for Visualization Simulation and Modeling Carleton University Canada

Integrated Cellular Framework for modeling Ecosystems: Theory and Applications', by Baha Uddin Kazi and Gabriel Wainer, published Online First on 11 March 2017 in the journal of simulation with the DOI: 10.1177/0037549717706007. In this paper, the funding statement was incorrect and the acknowledgements section was not added in the Online First version. This has since been corrected in the Online First version of the article.

关键词： Cell-DEVS modeling and simulation DEVS geographic information systems ecosystems

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A constructive method for approximating trigonometric functions and their integrals

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Applied Mathematics(A Journal of Chinese Universities) 2020年第3期35卷 293-307页

作者： CHEN Xiao-diao WANG Long-quan WANG Yi-gang Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi UniversityHangzhou 310027China

This paper presents an interpolation-based method(IBM)for approximating some trigonometric functions or their integrals as *** provides two-sided bounds for each function,which also achieves much better approximation effects than those of prevailing *** principle,the IBM can be applied for bounding more bounded smooth functions and their integrals as well,and its applications include approximating the integral of sin(x)/x function and improving the famous square root inequalities.

关键词： Padéapproximant trigonometric function constructive method interpolation-based method two-sided bounds

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A PARALLEL DOMAIN DECOMPOSITION METHOD FOR SOLVING ELLIPTIC EQUATIONS ON MANIFOLDS

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SIAM Journal on Scientific Computing 2025年第2期47卷 A916-A942页

作者： Qin, Lizhen Wang, Feng Wang, Yun School of Mathematics Nanjing University Nanjing210093 China Key Laboratory of Numerical Simulation of Large Scale Complex Systems Nanjing Normal University Ministry of Education Nanjing210023 China Jiangsu International Joint Laboratory of Big Data Modeling Computing and Application Nanjing Normal University Nanjing210023 China School of Mathematical Sciences Nanjing Normal University Nanjing210023 China School of Mathematical Sciences Center for Dynamical Systems and Differential Equations Soochow University Suzhou215006 China

We propose a new numerical domain decomposition method for solving elliptic equations on compact Riemannian manifolds. One advantage of this method is its ability to bypass the need for global triangulations or grids on the manifolds. Additionally, it features a highly parallel iterative scheme. To verify its efficacy, we conduct numerical experiments on some four-dimensional manifolds without and with boundary. © 2025 Society for Industrial and Applied Mathematics Publications. All rights reserved.

关键词： Domain decomposition methods

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Mechanical performance of recycled PVC window frames: An experimental and numerical investigation

Hybrid Advances

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Hybrid Advances 2025年 9卷

作者： Ait Khouya, Oumaima Sebbar, EL Hassan Elfarissi, Latifa Laaroussi, Najma University Hassan II of Casablanca Laboratory of modeling and Simulation of Intelligent Industrial Systems ENSET Mohammedia Morocco Technical Center of Plastic and Rubber Casablanca Morocco Institute for Research in Solar Energy and New Energies-IRESEN Morocco University Mohammed V in Rabat Material Energy and Acoustics Team (MEAT) EST Salé Morocco

PVC window frames are commonly used in the construction industry due to their durability, low cost, and ease of maintenance. However, with growing environmental concerns and the shift towards a circular economy, replacing virgin PVC with recycled materials in such applications has become a critical area of research. The recycling process as well as the source of waste, highly impact the quality of the recycled materials which limits its use in high-quality products. This study investigates the mechanical characterization of window profiles made from recycled PVC, focusing on their ability to withstand structural loads. Given that window frames are exposed to wind forces and building loads, ensuring their mechanical resistance is essential. The bending and tensile behavior of recycled PVC specimens were tested experimentally and numerically to assess the structural performance of the material under different loading conditions. A comparison between the results of numerical finite element simulations and those of experiments has been carried out to validate the findings. The results show that recycled PVC offers adequate mechanical and thermal performance for use in the manufacture of window profiles. © 2025

关键词： Circular economy Plastic recycling PVC PVC profile Window frame

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Dynamic analysis of rigid-flexible coupling spacecraft based on Euler parameters

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Scientific Reports 2025年第1期15卷 1-12页

作者： Ji, Yi Zhang, Huan School of Astronautics Harbin Institute of Technology Harbin 150001 China Frontier Science Center for Interaction between Space Environment and Matter Harbin 150001 China National Key Laboratory of Modeling and Simulation for Complex Systems Harbin 150001 China MOE Key Laboratory of Dynamics and Control of Flight Vehicle Beijing Institute of Technology Beijing 100081 China

With the development of aerospace technology, rigid-flexible coupling spacecraft with strong nonlinearity dominates, bringing huge challenges for numerical tools. This paper aims to accurately and quickly analyze the dynamic behavior of rigid-flexible coupling spacecraft. In our work, rigid body and flexible body are both described by Euler parameters for avoiding singular angles. Then, for this type of strong nonlinear dynamic system, the BN-stable method that is unconditionally stable for nonlinear initial value problems proposed by the first author is introduced to solve the transient responses. To keep the accuracy of the numerical rotation matrix, the relation between the angular velocity and Euler parameters, and the constraint in the level of velocity, are introduced to reformulate the original BN-stable method. Through the dynamic analysis for rigid satellite bodies and flexible solar wings, we find that the proposed strategy can effectively simulate the dynamic responses of spacecraft, and compared to the currently popular strategy, our strategy enjoys considerable advantages in accuracy, stability, and dissipation. © The Author(s) 2025.

关键词： BN-stability Dynamic analysis Euler parameters Rigid-flexible coupling Rotation matrix

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Artificial intelligence-based system frequency response modeling considering contribution of inverter-based resources

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Neural Computing and Applications 2024年 1-12页

作者： Feizi, Amir Golpîra, Hêmin Power Systems Modeling & Simulation Lab. Department of Electrical Engineering University of Kurdistan Kurdistan Sanandaj Iran

This paper proposes an artificial intelligence-based approach to address the contribution of inverter-based resources (IBRs) in the system frequency response (SFR) model. IBRs are assumed to be aggregated within a dynamic virtual power plant (DVPP), a new entity that can be summoned by the system operator to provide ancillary services. Current SFR models in the presence of IBRs are computationally expensive and neglect the synchronization dynamics between conventional synchronous generators (SGs) and IBRs. In conventional SFR models, the interactions between SGs were formulated through a unique synchronization coefficient. However, in modern power systems, the interaction between SGs and IBRs within DVPPs should be represented by a 2 × 2 synchronization coefficients (SCs) matrix. Hence, an attempt is made to deal with the calculation of the SCs matrix using optimization algorithms and a neural network. More precisely, optimization algorithms are employed to calculate the SCs at different prespecified operating points, which are then fed into a neural network for training purposes, enabling online SFR derivation. The proposed approach is characterized by its low computational burden and complexity, which are critical for accommodating different levels of DVPP penetration. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Virtual Power Plants

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