APA
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Ma’arif, A., Rahmaniar, W., Vera, M. A. M., Nuryono, A. A., Majdoubi, R., & Çakan, A. (2021). Artificial Potential Field Algorithm for Obstacle Avoidance in UAV Quadrotor for Dynamic Environment. 2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT).
Chicago/Turabian
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Ma’arif, A., Wahyu Rahmaniar, M. A. M. Vera, Aninditya Anggari Nuryono, Rania Majdoubi, and Abdullah Çakan. “Artificial Potential Field Algorithm for Obstacle Avoidance in UAV Quadrotor for Dynamic Environment.” 2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT) (2021).
MLA
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Ma’arif, A., et al. “Artificial Potential Field Algorithm for Obstacle Avoidance in UAV Quadrotor for Dynamic Environment.” 2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT), 2021.
BibTeX Click to copy
@article{a2021a,
title = {Artificial Potential Field Algorithm for Obstacle Avoidance in UAV Quadrotor for Dynamic Environment},
year = {2021},
journal = {2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT)},
author = {Ma’arif, A. and Rahmaniar, Wahyu and Vera, M. A. M. and Nuryono, Aninditya Anggari and Majdoubi, Rania and Çakan, Abdullah}
}
Artificial potential field (APF) is the effective real-time guide, navigation, and obstacle avoidance for UAV Quadrotor. The main problem in APF is local minima in an obstacle or multiple obstacles. In this paper, some modifications and improvements of APF will be introduced to solve one-obstacle local minima, two-obstacle local minima, Goal Not Reachable Near Obstacle (GNRON) and dynamic obstacle. The result shows that the improved APF gave the best result because it made the system reach the goal position in all of the examinations. Meanwhile, the APF with virtual force has the fastest time to reach the goal; however, it still has a problem in GNRON. It can be concluded that the APF needs to be modified in its algorithm to pass all of the local minima problems.
