Browsing by Author "Olivier, Paul"

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    Pose estimation through two non-overlapping orthogonally mounted cameras for fiducial markers.
    (Stellenbosch : Stellenbosch University, 2024-02) Olivier, Paul; Smit, WJ; Stellenbosch University. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering.
    ENGLISH ABSTRACT: This thesis explores the use of ArUco markers for precise pose estimation in Concentrated Solar Power (CSP) plants, aiming to enhance the accuracy and functionality of Unmanned Aerial Vehicles (UAVs) within these environments. The study is structured around three main objectives: assessing and implementing the Gazebo simulation engine’s applicability to real-world scenarios to create a tested for the next two objectives, creating a framework for selecting optimal markers, and evaluating different camera setups for improved system performance. Key findings include the successful validation of the Gazebo engine for simulating UAV operations. The research further delves into marker selection criteria, addressing aspects such as accuracy, focal length, resolution, and the impact of motion blur as well as giving insights into the operating distance and angle for different camera-marker configurations. Additionally, the comparative analysis of monocular, stereo, and orthogonal camera configurations reveals no significant performance disparity, suggesting that resolution adjustments for a monocular camera could mitigate the benefits of more complex setups. Although ArUco markers show promise for CSP applications, the study acknowledges potential limitations related to UAV operational distances and marker scalability. The conclusions drawn show the importance of tailored technological solutions, suggesting the incorporation of advanced sensor fusion and filtering strategies for enhanced system precision. Recommendations for future work include improving Gazebo’s simulation accuracy by adding motion blur effects and expanding the analysis to cover a wider range of focal lengths and marker sizes, aiming for a closer approximation to real-world conditions.