The main goal of the thesis is to study methods to follow row-like structures in agricultural scenarios by using low-cost hardware components to create an environment-aware robotic system. The objective is not only to solve a particular agricultural application, but the focus is to develop algorithms to understand the environment by using different sensors and allowing a robot to calculate and execute safe movement trajectories in any dynamically changing environment where plants are organized in a row. This thesis has developed an automatic crop row following system to perform navigation in very tightly spaced polytunnels and in hilly strawberry fields. The method to build a virtual barrier around the row-like structures allows the robot to find safe trajectories throughout a dynamically changing environment. The work eventually evolved in using deep learning approaches to recognize crop and non-crop regions for automated guiding line estimation. The thesis concludes that commercially available hardware can be integrated using advanced algorithms to precisely follow the rows and make quick estimations to adversely changing situations. A 2D Laser scanner, RTK-GNSS and 3D cameras with the agricultural robot named “Thorvald”, were used to perform all the experiments in real-world conditions. ; Hovedmålet med oppgaven er å følge radlignende strukturer i landbruket der man bruker billige maskinvarekomponenter for å lage et robotsystem som er bevisst på sine omgivelser. Målet er ikke bare å løse en bestemt landbruksapplikasjon, men fokuset er å utvikle algoritmer for å forstå omgivelsene ved å bruke kameraer og la roboten beregne og utføre baneplanlegging i et dynamisk miljø som er i endring. Denne oppgaven har utviklet et radfølgende navigastionsystem i trange polytunneller og i kuperte jordbærfelt. Videre muliggjør metoden å bygge visuelle barrierer rundt radene slik at roboten finner trygge områder i et dynamisk miljø i endring. Arbeidet benytter dype læringsmetoder for å gjenkjenne rader med planter ...


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    Title :

    Row following based navigation systems for agricultural robots ; Radfølgende navigasjonssystemer for landruksroboter



    Publication date :

    2021-01-01


    Type of media :

    Theses


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




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