OBSTACLE AVOIDANCE IN QUADCOPTER NAVIGATION USING MODIFIED LOCAL MEAN K-NEAREST CENTROID NEIGHBOR METHOD

  • Hendy Prasetyo Institut Teknologi Sepuluh Nopember (ITS)
  • Trihastuti Agustinah Institut Teknologi Sepuluh Nopember (ITS)

Abstract

Quadcopter is a type of Unmanned Aerial Vehicle (UAV) technology, characterized by simple mechanical structure, ease of flying and good maneuvering. In its usage, the quadcopter is required to evade obstacles in its path. Thus, an obstacle avoidance system in a 3D space with both static and dynamic obstacles is. Avoidance direction is determined by considering nearest distance based on the dimensions of the obstacle. Due to limited battery capacity, the quadcopter also needs to consider energy efficiency in obstacle avoidance. The obstacle’s properties and movement direction are also needed in considering the correct avoidance direction. Using a modified Local Mean K-Nearest Centroid Neighbor (LMKNCN) algorithm results in a 97.5% accuracy for avoidance direction decision. The learning process between training data and testing data yielded a computation duration of 0.142341 seconds. The simulations showed that the quadcopter is able to avoid static and dynamic obstacles to reach its destination without collisions.

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Author Biographies

Hendy Prasetyo, Institut Teknologi Sepuluh Nopember (ITS)
Department of Electrical Engineering
Trihastuti Agustinah, Institut Teknologi Sepuluh Nopember (ITS)
Department of Electrical Engineering

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Published
2022-07-31
How to Cite
PRASETYO, Hendy; AGUSTINAH, Trihastuti. OBSTACLE AVOIDANCE IN QUADCOPTER NAVIGATION USING MODIFIED LOCAL MEAN K-NEAREST CENTROID NEIGHBOR METHOD. Jurnal Ilmiah Kursor, [S.l.], v. 11, n. 3, p. 109, july 2022. ISSN 2301-6914. Available at: <https://kursorjournal.org/index.php/kursor/article/view/267>. Date accessed: 08 dec. 2022. doi: https://doi.org/10.21107/kursor.v11i3.267.
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Articles