Abstract
Unmanned Aerial Vehicles (UAVs) have been utilized in various applications in many fields in recent years. The paths the pilots flew can be measured and collected to be utilized to create routes for autonomous flight. However, there is a problem in that GPS errors result in the path being irregularly represented. The measured path can be optimized by using the Douglas-Peucker algorithm. Our research led to the proposal of a method to optimize this path by applying the Douglas-Peucker algorithm, which has been shown to be suitable for a two-dimensional path, in three-dimensional space. Optimization of the 3D path by the proposed method was possible by deleting unnecessary points from the three-dimensional space. Thus, the flight paths that were measured and collected can be utilized to define the autonomous flight path.
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Acknowledgments
This work was supported by the Korea Foundation for the Advancement of Science & Creativity (KOFAC), and funded by the Korean Government (MOE).
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Sim, G., Chung, J., Sung, Y. (2017). 3D UAV Flying Path Optimization Method Based on the Douglas-Peucker Algorithm. In: Park, J., Chen, SC., Raymond Choo, KK. (eds) Advanced Multimedia and Ubiquitous Engineering. FutureTech MUE 2017 2017. Lecture Notes in Electrical Engineering, vol 448. Springer, Singapore. https://doi.org/10.1007/978-981-10-5041-1_10
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DOI: https://doi.org/10.1007/978-981-10-5041-1_10
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