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Motion planning of unmanned aerial vehicles in dynamic 3D space: a potential force approach

Published online by Cambridge University Press:  11 April 2022

Mohammad H. Garibeh ,
Ahmad M. Alshorman Open the ORCID record for Ahmad M. Alshorman [Opens in a new window] ,
Mohammad A. Jaradat ,
Ahmad Bani Younes  and
Maysa Khaleel
Mohammad H. Garibeh
Affiliation:
Department of Mechatronics Engineering, German Jordanian University, Amman, Jordan
Ahmad M. Alshorman*
Affiliation:
Mechanical Engineering Department, Jordan University of Science and Technology, Irbid, Jordan
Mohammad A. Jaradat
Affiliation:
Mechanical Engineering Department, Jordan University of Science and Technology, Irbid, Jordan Department of Mechanical Engineering, American University of Sharjah, Sharjah, UAE
Ahmad Bani Younes
Affiliation:
Aerospace Engineering, San Diego State University, San Diego, CA, USA Department of Mechanical Engineering, Al-Hussein Technical University, Amman, Jordan
Maysa Khaleel
Affiliation:
Mechanical Engineering Department, Jordan University of Science and Technology, Irbid, Jordan
*
*Corresponding author. E-mail: amalshorman6@just.edu.jo
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Abstract

This research focuses on a collision-free real-time motion planning system for unmanned aerial vehicles (UAVs) in complex three-dimensional (3D) dynamic environments based on generalized potential force functions. The UAV must survive in such a complex heterogeneous environment while tracking a dynamic target and avoiding multiple stationary or dynamic obstacles, especially at low hover flying conditions. The system framework consists of two parts. The first part is the target tracking part employing a generalized extended attractive potential force into 3D space. In contrast, the second part is the obstacle avoidance part employing a generalized extended repulsive potential force into 3D space. These forces depend on the relative position and relative velocity between the UAV and respective obstacles. As a result, the UAV is attracted to a moving or stationary target and repulsed away from moving or static obstacles simultaneously in 3D space. Accordingly, it changes its altitude and projected planner position concurrently. A real-time implementation for the system is conducted in the SPACE laboratory to perform motion planning in 3D space. The system performance is validated in real-time experiments using three platforms: two parrot bebop drones and one turtlebot robot. The pose information of the vehicles is estimated using six Vicon cameras during real-time flights. The demonstrated results show the motion planning system’s effectiveness. Also, we propose a successful mathematical solution of the local minima problem associated with the potential field method in both stationary and dynamic environments.

Keywords

motion planningunmanned aerial vehiclesdynamic 3D spacepotential force
Type
Research Article
Information
Robotica , Volume 40 , Issue 10 , October 2022 , pp. 3604 - 3630
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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