Artificial Potential Field Algorithm for Obstacle Avoidance in UAV Quadrotor for Dynamic Environment

• Published in: 2021 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT) pp. 184 - 189
• Main Authors: Ma'Arif, Alfian, Rahmaniar, Wahyu, Vera, Marco Antonio Marquez, Nuryono, Aninditya Anggari, Majdoubi, Rania, Cakan, Abdullah
• Format: Conference Proceeding
• Language: English
• Published: IEEE 17-07-2021
• Subjects: Artificial Potential Field; Conferences; Dynamic Environment; Dynamics; Force; Heuristic algorithms; Obstacle Avoidance; Path Planning; Real-time systems; Satellite navigation systems; Satellites; Unmanned Aerial Vehicle
• DOI: 10.1109/COMNETSAT53002.2021.9530803

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.