This study covers the design of an autonomous robot and its testing process on an artificial maize field constructed for an indoor environment. However, the ultimate goal of this project was to participate in the Field Robot Event 2014 organized by the University of Hohenheim in Germany. This project was commissioned by HAMK University of Applied Sciences. And was fabricated and tested in the automation laboratory of HAMK UAS valkeakoski. The test result obtained by plotting the signal from wheel encoder, sonar sensor, gyroscope, magnetic compass was used as a primary source of information. Different scientific literature published on four wheel differential drive and vision based navigation was well examined for background information. Beside literature, rules and the regulation of the FRE 2014 were used as a source of information as well. In addition to these a working video on a previous field robot event provided a good reference for planning and designing an autonomous robot. A four-wheel differential drive chassis with a suspension system was designed and fabricated. Sensors such as a magnetic compass, gyroscope, sonar sensor, wheel encoder and camera were used to sense the environment. A suitable control algorithm was developed to meet the requirements of the competition. An indoor test field was designed with the artificial maize plants made up of paper and plastic tube. This test field was used to examine the control modules designed for different level. After a series of testing and tuning, a smooth navigation through row of corn was achieved. Oscillation was dropped down to nominal level; obstacle was identified from a safe distance and weed plants was successfully detected. The findings suggest that the performance of the robot is satisfactory. However, there are several possibilities for improving it. These include: replacing a sonar sensor with laser range scanner for detecting maize plants. Simultaneous localization and mapping can also be introduced. The author strongly recommends implementing a ...


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    Titel :

    Machine Design and Vision Based Navigation



    Erscheinungsdatum :

    01.01.2014


    Anmerkungen:

    10024/1769


    Medientyp :

    Hochschulschrift


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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