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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.


Experimental setup description.
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f12-sensors-15-16688: Experimental setup description.

Mentions: A solution to the overloading problem could be the use of an UAV acting as a remote sensor, as depicted in Figure 11d. The quadrotor should follow the vehicles, read the profile disposition inside the container and, through image processing, detect the relative distance between the harvester and the trailer, i.e., to minimize forage losses during the discharging process. A simple lab-scale system is utilized as proof-of-concept of the proposed solution. Figure 12 shows the setup platform used to emulate the tractor-trailer with the material. The emulated container has 2.0 × 1.5 × 1.0 m for length, width and height, respectively.


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)

Experimental setup description.
© Copyright Policy
Related In: Results  -  Collection

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

f12-sensors-15-16688: Experimental setup description.
Mentions: A solution to the overloading problem could be the use of an UAV acting as a remote sensor, as depicted in Figure 11d. The quadrotor should follow the vehicles, read the profile disposition inside the container and, through image processing, detect the relative distance between the harvester and the trailer, i.e., to minimize forage losses during the discharging process. A simple lab-scale system is utilized as proof-of-concept of the proposed solution. Figure 12 shows the setup platform used to emulate the tractor-trailer with the material. The emulated container has 2.0 × 1.5 × 1.0 m for length, width and height, respectively.

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.