Browsing by Person "Sharipov, Galibjon M."

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    Development and experimental validation of an agricultural robotic platform with high traction and low compaction
    (2023) Reiser, David; Sharipov, Galibjon M.; Hubel, Gero; Nannen, Volker; Griepentrog, Hans W.
    Some researchers expect that future agriculture will be automated by swarms of small machines. However, small and light robots have some disadvantages. They have problems generating interaction forces high enough to modify the environment (lift a stone, cultivate the soil, or transport high loads). Additionally, they have limited range and terrain mobility. One option to change this paradigm is to use spikes instead of wheels, which enter the soil to create traction. This allows high interaction forces with the soil, and the process is not limited by the weight of the vehicle. We designed a prototype for mechanical soil cultivation and weeding in agricultural fields and evaluated its efficiency. A static and dynamic test was performed to compare the energy input of the electrical motor with precise measurements of the forces on the attached tool. The results indicate that the prototype can create interaction forces of up to 2082 N with a robot weight of 90 kg. A net traction ratio of 2.31 was reached. The dynamic performance experiment generated pull forces of up to 1335 N for a sustained net traction ratio of 1.48. The overall energy efficiency ratio for the machine reached values of up to 0.54 based on the created draft force and the measured input energy consumption.
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    Position accuracy assessment of a uav-mounted sequoia+ multispectral camera using a robotic total station
    (2022) Paraforos, Dimitrios S.; Sharipov, Galibjon M.; Heiß, Andreas; Griepentrog, Hans W.
    Remote sensing data in agriculture that are originating from unmanned aerial vehicles (UAV)-mounted multispectral cameras offer substantial information in assessing crop status, as well as in developing prescription maps for site-specific variable rate applications. The position accuracy of the multispectral imagery plays an important role in the quality of the final prescription maps and how well the latter correspond to the specific spatial characteristics. Although software products and developed algorithms are important in offering position corrections, they are time- and cost-intensive. The paper presents a methodology to assess the accuracy of the imagery obtained by using a mounted target prism on the UAV, which is tracked by a ground-based total station. A Parrot Sequoia+ multispectral camera was used that is widely utilized in agriculture-related remote sensing applications. Two sets of experiments were performed following routes that go along the north–south and east–west axes, while the cross-track error was calculated for all three planes, but also three-dimensional (3D) space. From the results, it was indicated that the camera’s D-GNSS receiver can offer imagery with a 3D position accuracy of up to 3.79 m, while the accuracy in the horizontal plane is higher compared to the vertical ones.