Abstract
In order to improve the atmospheric environment monitoring mechanism and realize the construction of environmental maps, this paper proposes a proximity factor concentration fusion method for the problem of sub-map fusion to the construction of multiple rotorcrafts maps. The method refines the neighboring sub-maps to coincide with the boundary concentration factor and calculates the concentration factor of the overlapping area based on the factor mean algorithm to obtain a complete gas concentration map. The fusion of two sub-concentration maps is taken as an example in this paper. The two sub-concentration maps with short time difference before and after are fused into a map, and then the feasibility of the fusion method is verified by Fluent and Matlab simulation experiments, which provides the research foundation for the fusion of multiple gas concentration maps.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Zhu, J.H., Zhou, Y., et al.: Grid map mosaicing method based on image registration. Acta Automatica Sinica 41(02), 285–294 (2014)
Tang, H.W., Sun, W., et al.: Multi-robot raster map stitching method based on SURF feature. J. Electron. Meas. Instrum. 31(06), 859–868 (2017)
Ergin O.N., Levent, A.H.: Cooperative multi-robot map merging using fast-SLAM. In: Proceedings of Robolup (2009)
Monica, B., Arturo, G., Oscar, R., et al.: Alignment of visual maps in multi-robot Fast SLAM. In: Proceedings of the 8th WSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics (2009)
Wang, W., Pu, Y.M., Li, W.: A multi-robot 2D map fusion algorithm based on CI factor graph. Robotics 39(06), 872–878 (2017)
Liu, L.M., Cai, Z.X.: Research on multi-robot map fusion method. Microcomput. Syst. 33(09), 1934–1937 (2012)
Aragues, R., Cortes, J., Sagues, C.: Distributed consensus on robot networks for dynamically merging feature-based maps. IEEE Trans. Robot. 28(4), 840–854 (2012)
Zou, Y.H., Chen, W.H., Wang, J.H., Wu, X.M.: Multi-robot map fusion algorithm based on information gain consistency. Robot 36(05), 619–626 (2014)
Ma, X., Song, R., Guo, R., Li, Y.B.: Robotic grid map fusion based on immune adaptive genetic algorithm. Control Theory Appl. 26(09), 1004–1008 (2009)
Acknowledgements
This work is supported by four Projects from National Natural Science Foundation of China (60705035, 61075087, 61573263, 61273188), Scientific Research Plan Key Project of Hubei Provincial Department of Education (D20131105), and Project supported by the Zhejiang Open Foundation of the Most Important Subjects, also supported by Zhejiang Provincial Natural Science Foundation under Grant LY16F030007 and Hubei Province Science and Technology Support Project under Grant 2015BAA018.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Bao, P., Cheng, L., Wang, X., Liu, Q., Yu, Q. (2019). Multiple Rotorcrafts Environment Map Fusion for Atmosphere Monitoring. In: Fang, Q., Zhu, Q., Qiao, F. (eds) Advancements in Smart City and Intelligent Building. ICSCIB 2018. Advances in Intelligent Systems and Computing, vol 890 . Springer, Singapore. https://doi.org/10.1007/978-981-13-6733-5_10
Download citation
DOI: https://doi.org/10.1007/978-981-13-6733-5_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6732-8
Online ISBN: 978-981-13-6733-5
eBook Packages: EngineeringEngineering (R0)