Particle Filter SLAM for Vehicle Localization
DOI:
https://doi.org/10.5281/zenodo.10635489Keywords:
SLAM, Computer vision, Localization, Particle FilterAbstract
Simultaneous Localization and Mapping (SLAM) presents a formidable challenge in robotics, involving the dynamic construction of a map while concurrently determining the precise location of the robotic agent within an unfamiliar environment. This intricate task is further compounded by the inherent "chicken-and-egg" dilemma, where accurate mapping relies on a dependable estimation of the robot's location, and vice versa. Moreover, the computational intensity of SLAM adds an additional layer of complexity, making it a crucial yet demanding topic in the field. In our research, we address the challenges of SLAM by adopting the Particle Filter SLAM method. Our approach leverages encoded data and fiber optic gyro (FOG) information to enable precise estimation of vehicle motion, while lidar technology contributes to environmental perception by providing detailed insights into surrounding obstacles. The integration of these data streams culminates in the establishment of a Particle Filter SLAM framework, representing a key endeavor in this paper to effectively navigate and overcome the complexities associated with simultaneous localization and mapping in robotic systems.
Downloads
Metrics
References
Barfoot, Timothy D. State Estimation for Robotics. Cambridge: Cambridge University Press, 2017. Print.
Durrant-Whyte, Hugh, and Tim Bailey. "Simultaneous localization and mapping: part I." IEEE robotics & automation magazine 13.2 (2006): 99-110.
Bresson, Guillaume, et al. "Simultaneous localization and mapping: A survey of current trends in autonomous driving." IEEE Transactions on Intelligent Vehicles 2.3 (2017): 194-220.
Xiaobin, Liu, Yang Changlin, and Wang Wanting. "CARASSISTNET: DESIGN AND IMPLEMENTATION OF A DRIVING ASSISTANCE SYSTEM USING COMPUTER VISION." Ответственный редактор 28 (2023).
Zheng, Shuran, et al. "Simultaneous Localization and Mapping (SLAM) for Autonomous Driving: Concept and Analysis." Remote Sensing 15.4 (2023): 1156.
Guo, Cheng, et al. "THE ROLE OF MACHINE LEARNING IN ENHANCING COMPUTER VISION PROCESSING." АКТУАЛЬНЫЕ ВОПРОСЫ СОВРЕМЕННЫХ НАУЧНЫХ ИССЛЕДОВАНИЙ. 2023.
Kang, Haoyan, et al. "Secure Optical Hashing for Information Compression in a Convolutional Neural Network." 2023 IEEE Photonics Conference (IPC). IEEE, 2023.
Jia, Guanwei, et al. "Visual-SLAM Classical framework and key Techniques: A review." Sensors 22.12 (2022): 4582.
Zhao, Yufan, et al. "AN EXAMINATION OF TRANSFORMER: PROGRESS AND APPLICATION IN THE FIELD OF COMPUTER VISION." СОВРЕМЕННАЯ НАУКА: АКТУАЛЬНЫЕ ВОПРОСЫ, ДОСТИЖЕНИЯ И ИННОВАЦИИ. 2023.
Qiao, Yuxin, et al. "APPLICATION OF MACHINE LEARNING IN FINANCIAL RISK EARLY WARNING AND REGIONAL PREVENTION AND CONTROL: A SYSTEMATIC ANALYSIS BASED ON SHAP." WORLD TRENDS, REALITIES AND ACCOMPANYING PROBLEMS OF DEVELOPMENT 331 (2023).
YUXIN, QIAO, and N. FANGHAO. "COOPERATIVE GENERATIVE ADVERSARIAL NETWORKS: A DEEP DIVE INTO COLLABORATIVE INNOVATION IN GANS." СОВРЕМЕННЫЕ НАУЧНЫЕ ИССЛЕДОВАНИЯ: АКТУАЛЬНЫЕ ВОПРОСЫ 28 (2023).
Ni, Fanghao, Hengyi Zang, and Yuxin Qiao. "SMARTFIX: LEVERAGING MACHINE LEARNING FOR PROACTIVE EQUIPMENT MAINTENANCE IN INDUSTRY 4.0." The 2nd International scientific and practical conference “Innovations in education: prospects and challenges of today”(January 16-19, 2024) Sofia, Bulgaria. International Science Group. 2024. 389 p.. 2024.
Qiao, Yuxin, et al. "AUTOMATIC RECOGNITION OF STATIC PHENOMENA IN RETOUCHED IMAGES: A NOVEL APPROACH." The 1st International scientific and practical conference “Advanced technologies for the implementation of new ideas”(January 09-12, 2024) Brussels, Belgium. International Science Group. 2024. 349 p.. 2024.
QIAO, YUXIN, and FANGHAO NI. "RESEARCH ON THE INTERDISCIPLINARY APPLICATION OF COMPUTER VISION TECHNOLOGY IN INTELLIGENT AGRICULTURAL MACHINERY." АКТУАЛЬНЫЕ ВОПРОСЫ ОБЩЕСТВА, НАУКИ И ОБРАЗОВАНИЯ 3 (2023): 34.
Xu, Changxin, et al. "DEEP LEARNING IN PHOTOVOLTAIC POWER GENERATION FORECASTING: CNN-LSTM HYBRID NEURAL NETWORK EXPLORATION AND RESEARCH." The 3rd International scientific and practical conference “Technologies in education in schools and universities”(January 23-26, 2024) Athens, Greece. International Science Group. 2024. 363 p.. 2024.
Zhou, Hong, et al. "Improvement of Deep Learning Model for Gastrointestinal Tract Segmentation Surgery." Frontiers in Computing and Intelligent Systems 6.1 (2023): 103-106.
Xiong, Jize, et al. "Decoding Sentiments: Enhancing COVID-19 Tweet Analysis through BERT-RCNN Fusion." Journal of Theory and Practice of Engineering Science 4.01 (2024): 86-93.
Ye, Zhang, and Du Yukun. "MULTI-LEVEL FEATURE INTERACTION IN DUAL-MODAL OBJECT TRACKING: AN ADAPTIVE FUSION APPROACH." НАУЧНЫЕ ИССЛЕДОВАНИЯ 3 (2023): 31.
Zhang, Ye, and Yufan Zhao. "RESEARCH ON THE APPLICATION OF COMPUTER VISION IN INDUSTRIAL INSPECTION TECHNOLOGY." ФУНДАМЕНТАЛЬНАЯ И ПРИКЛАДНАЯ НАУКА: АКТУАЛЬНЫЕ ВОПРОСЫ ТЕОРИИ И ПРАКТИКИ. 2023.
Zhang, Ye, et al. "DeepGI: An Automated Approach for Gastrointestinal Tract Segmentation in MRI Scans." arXiv preprint arXiv:2401.15354 (2024).
Zhibin, Z. O. U., S. O. N. G. Liping, and Cheng Xuan. "Labeled box-particle CPHD filter for multiple extended targets tracking." Journal of Systems Engineering and Electronics 30.1 (2019): 57-67.
Zou, Zhibin, et al. "Scisrs: Signal cancellation using intelligent surfaces for radio astronomy services." GLOBECOM 2022-2022 IEEE Global Communications Conference. IEEE, 2022.
Zou, Zhibin, et al. "Unified characterization and precoding for non-stationary channels." ICC 2022-IEEE International Conference on Communications. IEEE, 2022.
Zou, Zhibin, et al. "Joint spatio-temporal precoding for practical non-stationary wireless channels." IEEE Transactions on Communications 71.4 (2023): 2396-2409.
Zou, Zhibin, Iresha Amarasekara, and Aveek Dutta. "Learning to Decompose Asymmetric Channel Kernels for Generalized Eigenwave Multiplexing."
Dong, Xinqi, et al. "The Prediction Trend of Enterprise Financial Risk based on Machine Learning ARIMA Model." Journal of Theory and Practice of Engineering Science 4.01 (2024): 65-71.
Zang, Hengyi, et al. "Evaluating the Social Impact of AI in Manufacturing: A Methodological Framework for Ethical Production." Academic Journal of Sociology and Management 2.1 (2024): 21-25.
Ma, Danqing, et al. "Implementation of computer vision technology based on artificial intelligence for medical image analysis." International Journal of Computer Science and Information Technology 1.1 (2023): 69-76.
Xu, Kunpeng, Lifei Chen, and Shengrui Wang. "A Multi-view Kernel Clustering framework for Categorical sequences." Expert Systems with Applications 197 (2022): 116637.
Xu, Kunpeng, Lifei Chen, and Shengrui Wang. "Data-driven Kernel Subspace Clustering with Local Manifold Preservation." 2022 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2022.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Journal of Industrial Engineering and Applied Science
This work is licensed under a Creative Commons Attribution 4.0 International License.
