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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.


UAV axes: (a) difference between absolute axes (X, Y, Z) and relative axes (x, y, z); (b) UAV displacement on the (x, y) plane with respect to the absolute plane.
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f7-sensors-15-16688: UAV axes: (a) difference between absolute axes (X, Y, Z) and relative axes (x, y, z); (b) UAV displacement on the (x, y) plane with respect to the absolute plane.

Mentions: The quadrotor's aerial movements are similar to those of a conventional helicopter. The quadrotor has four degrees of freedom (DOF): rotation over pitch, roll and yaw and translational movements over x, y and z, as depicted in Figure 7a. Notice that through rotational movement along the transversal y axis (pitch), translational movement on the x axis is achieved. A similar conclusion can be drawn for rotation over roll and translational movement on y.


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)

UAV axes: (a) difference between absolute axes (X, Y, Z) and relative axes (x, y, z); (b) UAV displacement on the (x, y) plane with respect to the absolute plane.
© Copyright Policy
Related In: Results  -  Collection

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

f7-sensors-15-16688: UAV axes: (a) difference between absolute axes (X, Y, Z) and relative axes (x, y, z); (b) UAV displacement on the (x, y) plane with respect to the absolute plane.
Mentions: The quadrotor's aerial movements are similar to those of a conventional helicopter. The quadrotor has four degrees of freedom (DOF): rotation over pitch, roll and yaw and translational movements over x, y and z, as depicted in Figure 7a. Notice that through rotational movement along the transversal y axis (pitch), translational movement on the x axis is achieved. A similar conclusion can be drawn for rotation over roll and translational movement on y.

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.