Improving Hexapod Platform Pose Accuracy - A Photogrammetry-Based Approach

The aim of this research is to make a newly constructed Stewart-Gough Platform-based test frame Tiger 66.1 operational by developing control software and estimating the error in its pose accuracy. The accuracy of the platform is affected by one source or multiple sources. The typical error sources are kinematic and structural, some of them originate from manufacturing imperfections, assembly deviations, elastic deformations, thermal deformations, and joint clearances which change the expected kinematic behavior of the manipulator. Also, some non-mechanical errors like transmission error, sensor accuracy, algorithm error, and truncation error in calculation contribute significantly in some cases. Using pose deviations as a foundation, this research further aims to develop a calibration method that enhances pose accuracy, leveraging the pose deviations observed during the initial measurements. This research presents a novel calibration method for a Stewart-Gough platform using photogrammetry, a digital image-based technique for 3D measurement and modeling. As part of this research, a new forward kinematic algorithm has been developed to implement an accurate non-contact calibration method that can improve the accuracy and precision of a general Stewart-Gough platform. The Stewart-Gough platform is one of the most popular Parallel Kinematic Machines (PKM). This mechanism, also known as a parallel manipulator or parallel robot, consists of a fixed base and a movable platform connected by six actuators or struts. The Stewart-Gough platform has remained an interesting machine for research due to its flexibility, structural rigidity, high accuracy, and reliability in motion control. The calibration of a Stewart-Gough platform is one of the essential steps in ensuring the accuracy and stability of the moving platform center. This dissertation investigates a forward kinematic calibration method for improving the accuracy of the Stewart-Gough platform-based test platform “Tiger 66.1” which is intended for use in the characterization of additively manufactured parts, although the method is not restricted to this platform only and can be extended to any similar platforms designed for use in various applications. For calibrating Tiger 66.1, a new forward kinematic algorithm has been developed in this research. The forward kinematics for parallel manipulator generates multiple solutions and they include both feasible and unfeasible solutions. The developed algorithm is a new way of finding unique feasible solution for a platform pose. The proposed algorithm utilizes the high power of modern computing systems and finds a unique solution for a pose through iterations. The advantage of this new algorithm is that the solution obtained from the iterations does not need to be verified manually to check the feasibility in real life and can be directly used as input for any further calculations without stopping the computation process. The proposed calibration methods used photogrammetry which minimizes the need for manual handling of the platform during the calibration process. Photogrammetry uses images of targets taken by one or more cameras to reconstruct 3D positions and orientations. In this research a high-resolution digital camera has been used to take multiple images of the moving platform center from three different angles for each pose and analyze those images through the commercial software package “Photomodeler”, to measure the pose of the platform in three-dimensional space. This method eliminates the need for any additional measurement instrument to be used directly or indirectly interacting with the Stewart-Gough platform. The proposed forward kinematic technique is validated through both simulations and experiments on the physical Stewart-Gough platform-based test frame Tiger 66.1. The vision-based approach is showcased to improve absolute positioning accuracy by up to 25% compared to an uncalibrated platform. The method requires minimal hardware modification and renders it highly suitable for precision application. It provides a practical approach to the calibration of parallel manipulators intended for high-precision tasks. The dissertation concludes by summarizing the contributions of this research, which includes the development of a novel photogrammetry-based calibration method that involves minimal hardware modification and full extrinsic calibration from vision data. The demonstration shows the substantial potential of the proposed method in augmenting the positioning performance of the Stewart-Gough platform tailored for precision applications. Furthermore, the work identifies the areas for further work, such as implementing an online calibration method. Overall, this research demonstrates the capabilities of photogrammetry for parallel manipulator calibration while minimizing hardware modifications, thereby presenting a pragmatic approach to the calibration of such systems in the pursuit of high-precision applications