Robot Navigation and Map Construction Based on SLAM Technology
DOI:
https://doi.org/10.53469/wjimt.2024.07(03).02Keywords:
SLAM technology, Map construction, Visual SLAM, Application scenarioAbstract
SLAM (Simultaneous Localization and Mapping) technology plays a crucial role in the field of robotics, which realizes the autonomous navigation of robots in unknown environments through real-time positioning, mapping and path planning. This paper first introduces the basic principle and workflow of SLAM technology, including sensor data fusion, state estimation and map construction. Then, by comparing and analyzing the map construction methods of traditional raster map and visual SLAM technology, the advantages and disadvantages of different map representations are shown. Finally, combined with the practical application scenario, the wide application of SLAM technology in logistics, intelligent manufacturing and other fields is discussed, and its future development direction is prospected.
References
Qian, Kun, et al. "Implementation of Artificial Intelligence in Investment Decision-making in the Chinese A-share Market." Journal of Economic Theory and Business Management 1.2 (2024): 36-42.
Bao, Q., Wei, K., Xu, J., & Jiang, W. (2024). Application of Deep Learning in Financial Credit Card Fraud Detection. Journal of Economic Theory and Business Management, 1(2), 51-57.
Biology-based AI Predicts T-cell Receptor Antigen Binding Specificity. (2024). Academic Journal of Science and Technology, 10(1), 23-27. https://doi.org/10.54097/wy28c490
Wu, Binbin, et al. "Enterprise Digital Intelligent Remote Control System Based on Industrial Internet of Things." (2024).
Pan, Y., Wu, B., Zheng, H., Zong, Y., & Wang, C. (2024, March). THE APPLICATION OF SOCIAL MEDIA SENTIMENT ANALYSIS BASED ON NATURAL LANGUAGE PROCESSING TO CHARITY. In The 11th International scientific and practical conference “Advanced technologies for the implementation of educational initiatives”(March 19–22, 2024) Boston, USA. International Science Group. 2024. 254 p. (p. 216).
Li, X., Zheng, H., Chen, J., Zong, Y., & Yu, L. (2024). User Interaction Interface Design and Innovation Based on Artificial Intelligence Technology. Journal of Theory and Practice of Engineering Science, 4(03), 1-8.
Zhou, Hong, et al. "Application of Conversational Intelligent Reporting System Based on Artificial Intelligence and Large Language Models." Journal of Theory and Practice of Engineering Science 4.03 (2024): 176-182.
Xu, Kangming, et al. "Intelligent Classification and Personalized Recommendation of E-commerce Products Based on Machine Learning." arXiv preprint arXiv:2403.19345(2024).
Shen, Xinyu, et al. "Biology-based AI Predicts T-cell Receptor Antigen Binding Specificity." Academic Journal of Science and Technology 10.1 (2024): 23-27.
Chen, B., Basak, S., Chen, P., Zhang, C., Perry, K., Tian, S., ... & Jin, R. (2022). Structure and conformational dynamics of Clostridioides difficile toxin A. Life science alliance, 5(6).
Zhou, Tong. "Improved sales forecasting using trend and seasonality decomposition with lightgbm." 2023 6th International Conference on Artificial Intelligence and Big Data (ICAIBD). IEEE, 2023.
Xu, J., Wu, B., Huang, J., Gong, Y., Zhang, Y., & Liu, B. (2024). Practical Applications of Advanced Cloud Services and Generative AI Systems in Medical Image Analysis. arXiv preprint arXiv:2403.17549.
Yu, D., Xie, Y., An, W., Li, Z., & Yao, Y. (2023, December). Joint Coordinate Regression and Association For Multi-Person Pose Estimation, A Pure Neural Network Approach. In Proceedings of the 5th ACM International Conference on Multimedia in Asia (pp. 1-8).
Chen, B., Zhu, Y., Ye, S., & Zhang, R. (2018). Structure of the DNA-binding domain of human myelin-gene regulatory factor reveals its potential protein-DNA recognition mode. Journal of structural biology, 203(2), 170-178.
Zhang, Y., Liu, B., Gong, Y., Huang, J., Xu, J., & Wan, W. (2024). Application of Machine Learning Optimization in Cloud Computing Resource Scheduling and Management. arXiv preprint arXiv:2402.17216.
Gong, Y., Huang, J., Liu, B., Xu, J., Wu, B., & Zhang, Y. (2024). Dynamic Resource Allocation for Virtual Machine Migration Optimization using Machine Learning. arXiv preprint arXiv:2403.13619.
Chen, B., Liu, Z., Perry, K., & Jin, R. (2022). Structure of the glucosyltransferase domain of TcdA in complex with RhoA provides insights into substrate recognition. Scientific reports, 12(1), 9028.
Ni, Chunhe, et al. "Enhancing Cloud-Based Large Language Model Processing with Elasticsearch and Transformer Models." arXiv preprint arXiv:2403.00807 (2024).
Xu, J., Zhu, B., Jiang, W., Cheng, Q., & Zheng, H. (2024, April). AI-BASED RISK PREDICTION AND MONITORING IN FINANCIAL FUTURES AND SECURITIES MARKETS. In The 13th International scientific and practical conference “Information and innovative technologies in the development of society”(April 02–05, 2024) Athens, Greece. International Science Group. 2024. 321 p. (p. 222).
Xu, Z., Yuan, J., Yu, L., Wang, G., & Zhu, M. (2024). Machine Learning-Based Traffic Flow Prediction and Intelligent Traffic Management. International Journal of Computer Science and Information Technology, 2(1), 18-27.
Ding, Weike, et al. "Automated Compatibility Testing Method for Distributed Software Systems in Cloud Computing." (2024).
Shen, Xinyu, et al. "Biology-based AI Predicts T-cell Receptor Antigen Binding Specificity." Academic Journal of Science and Technology 10.1 (2024): 23-27.
Su, G., Wang, J., Xu, X., Wang, Y., & Wang, C. (2024). The Utilization of Homomorphic Encryption Technology Grounded on Artificial Intelligence for Privacy Preservation. International Journal of Computer Science and Information Technology, 2(1), 52-58.
Allman, R., Mu, Y., Dite, G. S., Spaeth, E., Hopper, J. L., & Rosner, B. A. (2023). Validation of a breast cancer risk prediction model based on the key risk factors: family history, mammographic density and polygenic risk. Breast Cancer Research and Treatment, 198(2), 335-347.
Lei, H., Chen, Z., Yang, P., Shui, Z., & Wang, B. (2024). Real-time Anomaly Target Detection and Recognition in Intelligent Surveillance Systems based on SLAM.
Wang, Y., Zhu, M., Yuan, J., Wang, G., & Zhou, H. (2024). The intelligent prediction and assessment of financial information risk in the cloud computing model. arXiv preprint arXiv:2404.09322.
Wang, B., He, Y., Shui, Z., Xin, Q., & Lei, H. Predictive Optimization of DDoS Attack Mitigation in Distributed Systems using Machine Learning.
Tian, J., Li, H., Qi, Y., Wang, X., & Feng, Y. Intelligent Medical Detection and Diagnosis Assisted by Deep Learning.
Zhou, Y., Zhan, T., Wu, Y., Song, B., & Shi, C. RNA Secondary Structure Prediction Using Transformer-Based Deep Learning Models.
He, Zheng, et al. "Application of K-means clustering based on artificial intelligence in gene statistics of biological information engineering."
Tian, J., Qi, Y., Li, H., Feng, Y., & Wang, X. (2024). Deep Learning Algorithms Based on Computer Vision Technology and Large-Scale Image Data. Journal of Computer Technology and Applied Mathematics, 1(1), 109-115.