Towards the Development of a Smart Flying Sensor: Illustration in the Field of Precision Agriculture

Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Vol. 15; no. 7; pp. 16688 - 16709
Main Authors: Hernandez, Andres, Murcia, Harold, Copot, Cosmin, De Keyser, Robin
Format: Journal Article
Language:English
Published: Switzerland MDPI AG 10.07.2015
MDPI
Subjects:
Aerospace & aeronautics engineering
Analytical Chemistry
Atomic and Molecular Physics, and Optics
Automation
Biochemistry
Control algorithms
Costs
Design and implementations
Electrical and Electronic Engineering
Engineering, computing & technology
Inertial measurement unit
Ingénierie aérospatiale
Ingénierie, informatique & technologie
Instrumentation
Path following control
Position estimation
precision agriculture
Product quality
Remote sensing
remote sensor
Remote sensors
Scale system
Sensors
Surveillance
Time delay compensation
UAV
Unmanned aerial vehicles
Vehicles
remote sensor
precision agriculture
UAV
ISSN:1424-8220, 1424-3210, 1424-8220
Online Access:Get full text
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Summary:Sensing is an important element to quantify productivity, product quality and to make decisions. Applications, such as mapping, surveillance, exploration and precision agriculture, require a reliable platform for remote sensing. This paper presents the first steps towards the development of a smart flying sensor based on an unmanned aerial vehicle (UAV). The concept of smart remote sensing is illustrated and its performance tested for the task of mapping the volume of grain inside a trailer during forage harvesting. Novelty lies in: (1) the development of a position-estimation method with time delay compensation based on inertial measurement unit (IMU) sensors and image processing; (2) a method to build a 3D map using information obtained from a regular camera; and (3) the design and implementation of a path-following control algorithm using model predictive control (MPC). Experimental results on a lab-scale system validate the effectiveness of the proposed methodology.
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scopus-id:2-s2.0-84940197709
ISSN:1424-8220
1424-3210
1424-8220
DOI:10.3390/s150716688