Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method
An essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueli...
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doaj-210d8c27ff084e929c2ba8117bd517612020-11-25T00:38:34ZengMDPI AGSensors1424-82202015-05-01155109481097210.3390/s150510948s150510948Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking MethodChao-I Chen0Robert Koseluk1Chase Buchanan2Andrew Duerner3Brian Jeppesen4Hunter Laux5Advanced Scientific Concepts Inc., 135 East Ortega Street, Santa Barbara, CA 93101, USAAdvanced Scientific Concepts Inc., 135 East Ortega Street, Santa Barbara, CA 93101, USAAdvanced Scientific Concepts Inc., 135 East Ortega Street, Santa Barbara, CA 93101, USAAdvanced Scientific Concepts Inc., 135 East Ortega Street, Santa Barbara, CA 93101, USAAdvanced Scientific Concepts Inc., 135 East Ortega Street, Santa Barbara, CA 93101, USAAdvanced Scientific Concepts Inc., 135 East Ortega Street, Santa Barbara, CA 93101, USAAn essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by combining sensitivity adjustments of a 3D Flash LIDAR camera with computer vision based image-processing techniques. The method overcomes the inherit ambiguity issues when reconstructing 3D information from traditional 2D images by taking advantage of ready to use 3D point cloud data from the camera, followed by well-established computer vision techniques. These techniques include curve fitting algorithms and outlier removal with the random sample consensus (RANSAC) algorithm to reliably estimate the drogue center in 3D space, as well as to establish the relative position between the probe and the drogue. To demonstrate the feasibility of the proposed method on a real system, a ground navigation robot was designed and fabricated. Results presented in the paper show that using images acquired from a 3D Flash LIDAR camera as real time visual feedback, the ground robot is able to track a moving simulated drogue and continuously narrow the gap between the robot and the target autonomously.http://www.mdpi.com/1424-8220/15/5/109483D Flash LIDARautonomous aerial refuelingcomputer visionUAVprobe and droguemarkerless |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chao-I Chen Robert Koseluk Chase Buchanan Andrew Duerner Brian Jeppesen Hunter Laux |
spellingShingle |
Chao-I Chen Robert Koseluk Chase Buchanan Andrew Duerner Brian Jeppesen Hunter Laux Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method Sensors 3D Flash LIDAR autonomous aerial refueling computer vision UAV probe and drogue markerless |
author_facet |
Chao-I Chen Robert Koseluk Chase Buchanan Andrew Duerner Brian Jeppesen Hunter Laux |
author_sort |
Chao-I Chen |
title |
Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method |
title_short |
Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method |
title_full |
Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method |
title_fullStr |
Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method |
title_full_unstemmed |
Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method |
title_sort |
autonomous aerial refueling ground test demonstration—a sensor-in-the-loop, non-tracking method |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2015-05-01 |
description |
An essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by combining sensitivity adjustments of a 3D Flash LIDAR camera with computer vision based image-processing techniques. The method overcomes the inherit ambiguity issues when reconstructing 3D information from traditional 2D images by taking advantage of ready to use 3D point cloud data from the camera, followed by well-established computer vision techniques. These techniques include curve fitting algorithms and outlier removal with the random sample consensus (RANSAC) algorithm to reliably estimate the drogue center in 3D space, as well as to establish the relative position between the probe and the drogue. To demonstrate the feasibility of the proposed method on a real system, a ground navigation robot was designed and fabricated. Results presented in the paper show that using images acquired from a 3D Flash LIDAR camera as real time visual feedback, the ground robot is able to track a moving simulated drogue and continuously narrow the gap between the robot and the target autonomously. |
topic |
3D Flash LIDAR autonomous aerial refueling computer vision UAV probe and drogue markerless |
url |
http://www.mdpi.com/1424-8220/15/5/10948 |
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