Article
Direct Entry Minimal Path UAV Loitering
Path Planning
Jay P. Wilhelm *, Garrett S. Clem and Gina M. Eberhart
Department of Mechanical Engineering, Russ College of Engineering and Technology, Ohio University, Athens,
OH 45701, USA; gc117711@ohio.edu (G.S.C.); ge646715@ohio.edu (G.M.E.)
* Correspondence: jwilhelm@ohio.edu; Tel.: +1-740-593-1508
† This paper is based on the results presented in Development of an Area of Interest Extended Coverage
Loitering Path Planner. In Proceedings of the AIAA Infotech@Aerospace, AIAA SciTech Forum, San Diego,
CA, USA, 4–8 January 2016.
Academic Editors: Javaan Chahl, David Anderson and Michael Wing
Received: 11 March 2017; Accepted: 4 April 2017; Published: 18 April 2017
Abstract:
Fixed Wing Unmanned Aerial Vehicles (UAVs) performing Intelligence, Surveillance
and Reconnaissance (ISR) typically fly over Areas of Interest (AOIs) to collect sensor data of the
ground from the air. If needed, the traditional method of extending sensor collection time is to
loiter or turn circularly around the center of an AOI. Current Autopilot systems on small UAVs
can be limited in their feature set and typically follow a waypoint chain system that allows for
loitering, but requires that the center of the AOI to be traversed which may produce unwanted
turns outside of the AOI before entering the loiter. An investigation was performed to compare the
current loitering techniques against two novel smart loitering methods. The first method investigated,
Tangential Loitering Path Planner (TLPP), utilized paths tangential to the AOIs to enter and exit
efficiently, eliminating unnecessary turns outside of the AOI. The second method, Least Distance
Loitering Path Planner (LDLPP), utilized four unique flight maneuvers that reduce transit distances
while eliminating unnecessary turns outside of the AOI present in the TLPP method. Simulation
results concluded that the Smart Loitering Methods provide better AOI coverage during six mission
scenarios.
It was also
determined that the LDLPP method spends less time in transit between AOIs.
The reduction in required transit time could be used for surveying additional AOIs.
Keywords: path planning; UAV; loitering; AOI; POI
1. Introduction
The development of Fixed Wing Unmanned Aerial Vehicles (UAVs) as surveillance tools has
grown exponentially in remote sensing applications [
1
,
2
]. The militarization of remote sensing UAVs
has been to said reduce risk and workload on soldiers as well as improve reconnaissance efforts [
3
].
Small (Group 1) hand launched UAVs, such as the RQ-11 Raven [
4
,
5
], are limited to flying shorter
duration missions compared to the large UAVs and therefore efficiency of remote sensing is paramount.
Increasing the efficiency in path planning could potentially increase sensor coverage, which will
be the primary focus of this paper.
Loitering, the act of circling an Area of Interest (AOI), is commonly used during remote sensing.
Small UAV autopilots tend to initiate the loitering by flying directly through the center of the AOI,
also known as the Point of Interest (POI), prior to circling [
6
–
9
].The Pixhawk autopilot, developed by
3D-Robotics [
10
], can be programmed for fixed wing aircraft is a commonly used autopilot that has
this loitering feature. This loitering behavior will be referred to as the Fly Through method for the
remainder of the paper. The loiter is programmed into the autopilot system as a number of waypoints
that pass directly through the POI and circle around until an overlap with the AOI is accomplished,
Aerospace 2017, 4, 23; doi:10.3390/aerospace4020023 www.mdpi.com/journal/aerospace
