@inproceedings{dc98f2039eda4c73925df5c9f996f518,
title = "Heuristic Guided Artificial Potential Field for Avoidance of Small Obstacles",
abstract = "In this paper, a modified heuristic guided Artificial Potential Field (APF) based algorithm has been proposed to find a practical trajectory for an Autonomous Unmanned Aerial Vehicle (UAV) path planning. The local minima are encountered in the conventional APF algorithm due to the cancellation of attractive and repulsive potential while avoiding unknown obstacles within the desired path, which results in the trapping of the agent before reaching the goal. Consequently, the traditional APF technique is therefore no longer advantageous in such cases. So in this proposed perpendicular approach based on APF helps to avoid such local minima. The advantage of the newly proposed method is the low computing time that lines up with the standard global path planner method. The proposed algorithm is tested and validated against existing general potential field techniques for different simulation scenarios in a 3D simulated environment using ROS and Gazebo supported PX4-SITL. The results have been presented for drone navigation and obstacle avoidance for the different scenarios in a simulated environment.",
keywords = "Artificial Potential Field, Local Minimum, Obstacle Avoidance, Path Planning, ROS, UAV",
author = "Sagar Dalai and Mahammad Irfan and Samarth Singh and Kaushal Kishore and Akbar, {S. A.}",
note = "Publisher Copyright: {\textcopyright} 2021 ICROS.; 21st International Conference on Control, Automation and Systems, ICCAS 2021 ; Conference date: 12-10-2021 Through 15-10-2021",
year = "2021",
doi = "10.23919/ICCAS52745.2021.9649879",
language = "English",
series = "International Conference on Control, Automation and Systems",
publisher = "IEEE Computer Society",
pages = "765--770",
booktitle = "2021 21st International Conference on Control, Automation and Systems, ICCAS 2021",
}