Sensor-Driven Area Coverage for an Autonomous Fixed-Wing Unmanned Aerial Vehicle

Abstract

Area coverage with an onboard sensor is an important task for an unmanned aerial vehicle (UAV) with many applications. Autonomous fixed-wing UAVs are more appropriate for larger scale area surveying since they can cover ground more quickly. However, their non-holonomic dynamics and susceptibility to disturbances make sensor coverage a challenging task. Most previous approaches to area coverage planning are offline and assume that the UAV can follow the planned trajectory exactly. In this paper, this restriction is removed as the aircraft maintains a coverage map based on its actual pose trajectory and makes control decisions based on that map. The aircraft is able to plan paths in situ based on sensor data and an accurate model of the on-board camera used for coverage. An information theoretic approach is used that selects desired headings that maximize the expected information gain over the coverage map. In addition, the branch entropy concept previously developed for autonomous underwater vehicles is extended to UAVs and ensures that the vehicle is able to achieve its global coverage mission. The coverage map over the workspace uses the projective camera model and compares the expected area of the target on the ground and the actual area covered on the ground by each pixel in the image. The camera is mounted on a two-axis gimbal and can either be stabilized or optimized for maximal coverage. Hardware-in-the-loop simulation results and real hardware implementation on a fixed-wing UAV show the effectiveness of the approach. By including the already developed automatic takeoff and landing capabilities, we now have a fully automated and robust platform for performing aerial imagery surveys.

Structure from Motion (SfM) Photogrammetry with Drone Data: A Low Cost Method for Monitoring Greenhouse Gas Emissions from Forests in Developing Countries

“…The Phantom flew 2 full autonomous missions at different altitudes (Table 1) in a parallel strip pattern in order to achieve adequate and consistent ground coverage [46]. The GoPro camera was configured to capture images at 0.5 s intervals in order to achieve an overlap of >80% (both end lap and side lap) [21].…”

Boustrophedon coverage path planning for UAV aerial surveys in wind

“…This area is normally represented by a polygon. CPP has been extensively studied in literature for use in a range of applications, for example lawn mowing, milling [9], cleaning robots [10], agricultural field machines [11], rotary wing surveys [12], and fixed wing surveys [13]. The simplest path that guarantees coverage of an area is a simple back and forth motion of the vehicle along the long axis of the polygon.…”

“…However as fixed wing aircraft are more susceptible to external disturbances like wind, and have to maintain forward motion to stay in the air, this means that accurate path following is made much more difficult. This is why in [13] the sweep method is not used but a method which guides the aircraft to areas which have not been photographed adequately using a camera model. While this ensured total coverage, the flight time was much longer and required the camera to be gimbaled, as the flight path involved many turns.…”

Design of Unmanned Vehicle System for Disaster Detection

“…These two vehicles often carry cameras to transmit images of the scene back to the command center via wireless network [3,[6][7][8][9]11]. They also can be operated by remote control [3,4,6,[8][9][10][11].…”

“…They also can be operated by remote control [3,4,6,[8][9][10][11]. But such vehicle equipment is very expensive and is difficult to obtain due to financial constraints of the local government [1].…”