A Dynamic Artificial Potential Field (D-APF) UAV Path Planning Technique for Following Ground Moving Targets

Abstract

Path planning is a vital and challenging component in the support of Unmanned Aerial Vehicles (UAVs) and their deployment in autonomous missions, such as following ground moving target. Few attempts are reported in the literature on multirotor UAV path planning techniques for following ground moving targets despite the great improvement in their control dynamics, flying behaviors and hardware specifications. These attempts suffer several drawbacks including their hardware dependency, high computational requirements, inability to handle obstacles and dynamic environments in addition to their low performance regarding the moving target speed variations. In this paper, a novel dynamic Artificial Potential Field (D-APF) path planning technique is developed for multirotor UAVs for following ground moving targets. The UAV produced path is a smooth and flyable path suitable to dynamic environments with obstacles and can handle different motion profiles for the ground moving target including change in speed and direction. Additionally, the proposed path planning technique effectively supports UAVs following ground moving targets while maneuvering ahead and at a standoff distance from the target. It is hardware-independent where it can be used on most types of multirotor UAVs with an autopilot flight controller and basic sensors for distance measurements. The developed path planning technique is tested and validated against existing general potential field techniques for different simulation scenarios in ROS and gazebo-supported PX4-SITL. Simulation results show that the proposed D-APF is better suited for UAV path planning for following moving ground targets compared to existing general APFs. In addition, it outperforms the general APFs as it is more suitable for UAVs flying in environments with dynamic and unknown obstacles.