In today's information society, the importance of collecting data through multiple channels continues to increase. Among them, the use of drones to collect information on large-area forests is in line with the modern green development concept. In actual drone collection tasks, it is crucial to ensure the accuracy of collected data and the safe flight of the drone. In order to deal with these challenges, a multi-sensor fusion algorithm based on Bayesian estimation is proposed to overcome the problems of insufficient data accuracy of a single sensor and data duplication and noise caused by simple fusion of multiple sensors. At the same time, considering the actual need for path planning without a global map when flying over a large area in the woods, a local grid mapping strategy based on sliding windows is proposed, that is, a moving map is established with the drone body as the map center to ensure the maintenance of a fixed map size. This strategy effectively reduces the memory usage problem and is consistent with the actual scenario of large-scale outdoor flight.


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    Title :

    Research on multisensor fusion UAV sensing strategy based on forest information collection


    Contributors:
    Wang, Hongzhi (editor) / Li, Wenlong (editor) / Du, Kang (author) / Song, Dalei (author)

    Conference:

    Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024) ; 2024 ; Wuhan, China


    Published in:

    Proc. SPIE ; 13210


    Publication date :

    2024-07-11





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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