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

Hernandez A, Murcia H, Copot C, De Keyser R - Sensors (Basel) (2015)

Bottom Line: Sensing is an important element to quantify productivity, product quality and to make decisions.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Energy, Systems and Automation (EeSA), Ghent University, 9000 Ghent, Belgium. Andres.Hernandez@ugent.be.

ABSTRACT
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.

No MeSH data available.


Camera characterization. Experimental data and approximation obtained for the (a) bottom and (b) frontal camera.
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f3-sensors-15-16688: Camera characterization. Experimental data and approximation obtained for the (a) bottom and (b) frontal camera.

Mentions: The cameras represent the main source of information for the system. Therefore, it is important to characterize the camera experimentally, in order to define the relation between pixels and meters. The experiment consists of taking pictures of a reference object of known characteristics (i.e., height, width and color) at different distances. A fitting procedure is performed in order to characterize the cameras using the experimental as depicted in Figure 3, thus obtaining a relation which allows to compute the distance between the quadrotor and a reference object using Equations (2) and (3).(2)Altitude[m]=148.6(PixelsArea)−0.339−0.8036(3)Distance[m]=599.3(PixelsArea)−0.5138−0.006038


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

Hernandez A, Murcia H, Copot C, De Keyser R - Sensors (Basel) (2015)

Camera characterization. Experimental data and approximation obtained for the (a) bottom and (b) frontal camera.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541901&req=5

f3-sensors-15-16688: Camera characterization. Experimental data and approximation obtained for the (a) bottom and (b) frontal camera.
Mentions: The cameras represent the main source of information for the system. Therefore, it is important to characterize the camera experimentally, in order to define the relation between pixels and meters. The experiment consists of taking pictures of a reference object of known characteristics (i.e., height, width and color) at different distances. A fitting procedure is performed in order to characterize the cameras using the experimental as depicted in Figure 3, thus obtaining a relation which allows to compute the distance between the quadrotor and a reference object using Equations (2) and (3).(2)Altitude[m]=148.6(PixelsArea)−0.339−0.8036(3)Distance[m]=599.3(PixelsArea)−0.5138−0.006038

Bottom Line: Sensing is an important element to quantify productivity, product quality and to make decisions.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical Energy, Systems and Automation (EeSA), Ghent University, 9000 Ghent, Belgium. Andres.Hernandez@ugent.be.

ABSTRACT
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.

No MeSH data available.