Generalized shape expansion-based motion planning in three-dimensional obstacle-cluttered environment

A study expands the SE-SCP algorithm and presents the generalized shape expansion (GSE) algorithm for a three-dimensional (3-D) environment. Contrary to the shape expansion performed by the SE-SCP, which is restricted to a spherical one with a small radius, the GSE algorithm helps in expansion over a generalized shape, which is the best representative of the free space in the overall workspace that helps in exploring the free space in a much more efficient way. That is why the word ‘generalized’ is used here. To this end, a sampling-based motion-planning algorithm has been presented, which explored a two-dimensional (2-D) workspace leveraging the novel GSE algorithm. It was found to explore the free space in a very efficient way, which was reflected in its computational advantage over several other existing seminal algorithms.