construction and control of an aerial vehicle for crop monitoring

88 Pages·2017·2.54 MB·English

CONSTRUCTION AND CONTROL
OF AN AERIAL VEHICLE FOR
CROP MONITORING
MASTER IN OPT OMECHATRONICS
A dvisor:

PhD. Gerardo Ramón Flores Colunga

Student:
Andrés Montes de Oca Rebolledo

July 2018
León, Guanajuato, México
Contents
Acknowledgements 9
Publications 10
Abstract 11
Introduction 14
1 Literature review 15
1.1 Commercial multispectral imaging systems . . . . . . . . . . . . . . . . 15
1.2 Aerial imaging system implementation and applications . . . . . . . . . 16
2 Theoretical knowledge 28
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.2 Quad-rotor Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.2.1 Airspeed and groundspeed . . . . . . . . . . . . . . . . . . . . . 30
2.2.2 Euler equations . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.2.3 Newton equations . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3 Multispectral properties of vegetation . . . . . . . . . . . . . . . . . . . 37
2
2.3.1 Optical aspect of photosynthesis and its relationship with vege-
tation stress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.3.2 Vegetation curve and spectral bands of vegetation . . . . . . . . 41
2.3.3 Vegetation indices . . . . . . . . . . . . . . . . . . . . . . . . . . 44
2.3.4 Normalized Difference Vegetation Index . . . . . . . . . . . . . . 45
3 Methodology 47
3.1 System description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.1.1 Hardware components . . . . . . . . . . . . . . . . . . . . . . . 49
3.1.2 Software components . . . . . . . . . . . . . . . . . . . . . . . . 50
3.2 Multispectral camera design . . . . . . . . . . . . . . . . . . . . . . . . 52
3.3 Flight trajectory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.3.1 Photogrammetric Parameters . . . . . . . . . . . . . . . . . . . 55
3.3.2 Camera Trigger System . . . . . . . . . . . . . . . . . . . . . . . 57
3.4 Image post-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.4.1 Georeferencing . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
3.4.2 Orthomosaic generation . . . . . . . . . . . . . . . . . . . . . . 59
3.4.3 NDVI computation . . . . . . . . . . . . . . . . . . . . . . . . . 59
4 Experiments 61
4.1 Camera testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.2 Photogrammetric parameters and flight plan . . . . . . . . . . . . . . . 65
4.3 Image post-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.3.1 Image rectification . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.3.2 Image Georeferencing . . . . . . . . . . . . . . . . . . . . . . . . 72
4.3.3 Orthomosaic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.3.4 NDVI computation . . . . . . . . . . . . . . . . . . . . . . . . . 73
4.4 Additional experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
5 Conclusions 78
3
Bibliography 79
4
List of Figures
1 The unmanned aerial vehicle used in this work. This drone is equipped
with the proposed multispectral imagery system. . . . . . . . . . . . . . 13
1.1 Commercial multispectral imaging systems. . . . . . . . . . . . . . . . . 16
1.2 Spectrometer-based hyperspectral sensor. . . . . . . . . . . . . . . . . . 17
1.3 Imaging system with external filters. . . . . . . . . . . . . . . . . . . . 19
1.4 Implementation of a multispectral imaging system for NDVI computation. 20
1.5 Multispectral imaging system implemented in a rotary-wing vehicle. . . 21
1.6 Hyperspectral imaging system implemented on a octa-rotor. . . . . . . 21
1.7 Imaging system implemented in a fixed-wing UAV platform. . . . . . . 22
1.8 NDVI obtained with a modified digital camera and a RedEdge-M. . . . 23
1.9 Orthomosaics obtained from aerial imagery. . . . . . . . . . . . . . . . 23
1.10 Aerial imaging system implemented in a fixed-wing platform. . . . . . . 24
1.11 Fixed-wing platform used in [1] to produce a 2D and 3D model of a
predefined area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
1.12 Hyperspectral imaging system used in [2]. . . . . . . . . . . . . . . . . 25
1.13 Quad-rotor for the implementation of an imaging system used in [3]. . . 26
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1.14 Platforms used for echohydrology application [4]. . . . . . . . . . . . . 26
1.15 Thermal imaging with a rotary-wing vehicle implemented in [5]. . . . . 27
2.1 Quad-rotor inertial and body frame. . . . . . . . . . . . . . . . . . . . . 29
2.2 Euler angles [6]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.3 Absorption spectra of chlorophyll and carotenoids. . . . . . . . . . . . . 39
2.4 Internal structure of a plant [7]. . . . . . . . . . . . . . . . . . . . . . . 40
2.5 Reflectance curves for vegetation at different stages [8]. . . . . . . . . . 41
2.6 Reflectance curve of vegetation [8]. . . . . . . . . . . . . . . . . . . . . 43
2.7 Extended reflectance curve of vegetation [9]. . . . . . . . . . . . . . . . 44
3.1 The overall aerial imaging system architecture. . . . . . . . . . . . . . . 48
3.2 Quad-rotor components equipped with the imaging system. . . . . . . . 49
3.3 Cameras mounting rig developed in the LAB. . . . . . . . . . . . . . . 51
3.4 Mission Planner. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.5 Quantum efficiency of the Aptina sensor. . . . . . . . . . . . . . . . . . 53
3.6 Wratten 25 transmission curve. . . . . . . . . . . . . . . . . . . . . . . 54
3.7 Graphic representation of overlaps. . . . . . . . . . . . . . . . . . . . . 56
3.8 Elements that integrate the trigger system : flight controller, microcom-
puter and cameras. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
4.1 Lenses of both cameras. . . . . . . . . . . . . . . . . . . . . . . . . . . 62
4.2 RGB image split into individual bands. . . . . . . . . . . . . . . . . . . 63
4.3 Near-infrared image split into the individual bands. . . . . . . . . . . . 64
4.4 Histogram of the three bands of a near-infrared reflectance image. Hor-
izontal axis represents pixel values (0 - 255) and vertical axis represents
frequency of values. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.5 NDVI computed with Fiji. . . . . . . . . . . . . . . . . . . . . . . . . . 66
4.6 Flight trajectory generated by Mission Planner. . . . . . . . . . . . . . 67
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4.7 Quad-rotor trajectory followed and points in space where the images are
captured. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
4.8 Images taken by the drone. . . . . . . . . . . . . . . . . . . . . . . . . . 70
4.9 Multispectral orthomosaics. . . . . . . . . . . . . . . . . . . . . . . . . 73
4.10 NDVI of a soccer field computed by Fiji. . . . . . . . . . . . . . . . . . 74
4.11 Manual trigger points on a park. . . . . . . . . . . . . . . . . . . . . . . 75
4.12 Orthomosaics of a park. . . . . . . . . . . . . . . . . . . . . . . . . . . 76
4.13 NDVI of a small area of a park computed by Fiji. . . . . . . . . . . . . 77
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List of Tables
3.1 Quad-rotor parameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.2 Camera parameters. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
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Acknowledgements
I would like to show my gratitude to Consejo Nacional de Ciencia y Tecnolog´ıa
(CONACYT) who brought me a Master scholarship, that was determinant in the de-
velopment and continuity of my project. I also want to thank the Academic authori-
´
ties of Centro de Investigaciones en Optica (CIO) who economically supported me to
participate in the International Conference on Unmanned Aircraft Systems this year.
Similarly I am very thankful with my advisor, Dr. Gerardo Flores, for his continuous
support.
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Publications
Concerence papers
• Low-cost multi-spectral imagery system for crop monitoring. A. Montes de
Oca, L. Arreola, A. Flores, J. Sanchez, G. Flores. International Conference on
Unmanned Aircraft Systems 2018 (ACCEPTED).
• Improvement in the UAV position estimation with low-cost GPS and vision-based
system: Application to a quad-rotor UAV. L. Arreola, A. Montes de Oca, A.
Flores, J. Sanchez, G. Flores. International Conference on Unmanned Aircraft
Systems 2018 (ACCEPTED).
• Nonlinear observer design for 1-DOF upper limb exoskeleton. Authors: J. Santis,
A. Flores, A. Montes de Oca, L. Arreola and G. Flores. Conference on Decision
and Control 2018 (UNDER REVIEW).
• Design of a simple controller for the flight mode transition of a hybrid drone.
Authors: A. Flores, J. Sanchez, A. Montes de Oca, L. Arreola and G. Flores.
Conference on Decision and Control 2018 (UNDER REVIEW).
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