magistrsko delo
Franci Ovčak (Author), Matjaž Mihelj (Mentor)

Abstract

Sodobno kmetijstvo se vse bolj usmerja proti digitalizaciji in robotizaciji z namenom zmanjšanja prekomerne uporabe pesticidov in gnojil ter hkratni povečavi količine pridelka. Ključno za uresničevanje teh ciljev je razumevanje fizikalnih in kemičnih lastnosti prsti, kar posledično pomeni potrebo po natančnem vzorčenju. Tradicionalne metode, kot so ročni odvzem vzorcev ali terenska analiza, so ob upoštevanju obsega zahtevanih meritev neekonomične in zahtevne. Zato je avtomatizacija tega procesa s pomočjo avtonomnih mobilnih vozil postala ključnega pomena. V okviru magistrskega dela se bomo posvetili izboljšavi in prenovi obstoječe mobilne platforme s poudarkom na integraciji sistema za lokalizacijo in navigacijo. Platformo bomo opremili z elektrodami, napravo za merjenje upornosti tal ter vrtalnikom za odvzem vzorcev. Ker ima lokalizacija ključno vlogo v tem kontekstu, bomo analizirali različne algoritme obdelave podatkov in izvedli njihovo medsebojno primerjavo. V nadaljevanju magistrskega dela podrobno obravnavamo mobilno platformo, njeno kinematiko in komponente. Osredotočamo se na upravljanje platforme, vodenje ter implementacijo algoritmov za združevanje podatkov iz senzorjev. Za določanje orientacije platforme bomo uporabili nepristranski Kalmanov filter (UKF), medtem ko bomo za določanje položaja in končne orientacije testirali tri pristope: razširjeni Kalmanov filter, dinamično ojačenje in filter delcev. Predstavili bomo vtičnik "teb local planner", glavne izzive pri njegovi uporabi ter predlagane rešitve. Nadalje opisujemo spletni vmesnik, ki je bil zasnovan za lažje delo s platformo. V zaključnih poglavjih obravnavamo validacijo algoritmov za lokalizacijo v simuliranem okolju in z realnimi podatki.

Keywords

vzorčenje prsti;mobilna robotika;ROS;lokalizacija;magisteriji;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UL FE - Faculty of Electrical Engineering
Publisher: [F. Ovčak]
UDC: 007.52(043.3)
COBISS: 165729027 Link will open in a new window
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Downloads: 15
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Other data

Secondary language: English
Secondary title: Control of a mobile robotic system for automated soil analysis
Secondary abstract: Modern agriculture is increasingly moving towards digitization and robotics to reduce the overuse of pesticides and fertilizers while increasing yields. Key to achieving these goals is an understanding of the physical and chemical properties of the soil, which in turn leads to the need for accurate soil sampling. Traditional methods, such as manual sampling or field analysis, are uneconomical and difficult given the scale of the measurements required. Therefore, the automation of this process by means of autonomous mobile vehicles (AMVs) has become crucial. In the framework of this master thesis, we will focus on the improvement and redesign of an existing mobile platform with a focus on the integration of a localization and navigation system. The platform will be equipped with electrodes, a device for measuring soil resistivity and a drill for sampling. As localization plays a key role in this context, we will analyse the different data processing algorithms and compare them with each other. In the remainder of the master thesis, we discuss in detail the mobile platform, its kinematics and components. We focus on the platform management, control and implementation of sensor data fusion algorithms. We use an unscented Kalman filter (UKF) to determine the orientation of the platform, while three approaches are tested to determine the position and final orientation: an extended Kalman filter, dynamic amplification and a particle filter. We will also present the "teb local planner" plugin, the main challenges in its use and the proposed solutions. We further describe the web interface that has been designed to facilitate working with the platform. In the final chapters, we discuss the validation of the localization algorithms in a simulated environment and with real data.
Secondary keywords: soil sampling;mobile robotics;ROS;localisation;navigation;
Type (COBISS): Master's thesis/paper
Study programme: 1000316
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za elektrotehniko
Pages: XXII, 81 str.
ID: 19872241