Computational analysis of a mobile path-planning via quarter-sweep two-parameter over-relaxation

Over the years, self-reliant navigation has risen to the forefront of research topics. Improving the path-planning competencies is an extremely important component in achieving excellent autonomous navigation. This paper describes a refinement of the proficiency of mobile path-planning through a computational approach, i.e. the quarter-sweep two-parameter over-relaxation (QSTOR), to solving path-planning problems iteratively. The solution of Laplace’s equation (otherwise known as the harmonic functions) is the source for producing the potential function of the configuration space of the mobile robot. Numerical experiments illustrate that, in a given environment, a mobile robot is able to steer towards a particular destination with a smooth and ideal path from any beginning location. Furthermore, it is shown that in terms of the iterations number and computational time, the QSTOR iterative technique outperforms its predecessors in addressing mobile path-planning issues.