Abstract
The Stewart-Gough platform (SGP) is a six degree-of-freedom (DOF) parallel manipulator whose reachable workspace is complex due to its closed-loop configuration and six DOF outputs. As such, methods of path planning that involve storing the entire reachable workspace in memory at high resolutions are not feasible due to this six-dimensional workspace. In addition, complete path planning algorithms struggle in higher dimensional applications without significant customisations. As a result, many workspace analysis algorithms and path planning schemes use iterative techniques, particularly when tracking the manipulator's many direct kinematic solutions. The aim of this paper is to present the viability of singularity-free path planning in the Stewart-Gough platform's 6-dimensional workspace on modern-day computing systems by demonstrating its assembly mode-changing capability. The entire workspace volume is found using flood-fill algorithms with smooth and singularity-free trajectories generated within this known workspace. Workspace volume analysis was also performed with results comparable to other works.
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