Heuristic Guided Artificial Potential Field for Avoidance of Small Obstacles

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.