Development of Path Optimization Using Quarter-Sweep Modified Successive Over-Relaxation Iterative Technique

Over time, self-reliant navigation has emerged as a prominent area of research. Enhancing path-planning abilities is crucial for achieving effective autonomous navigation. This paper presents a computational method, quarter-sweep modified successive over-relaxation (QSMSOR), to iteratively address mobile path-planning challenges. The proposed technique utilizes red–black ordering and incorporates four weighted parameters. By solving Laplace’s equation, the potential function of the mobile robot’s configuration space is generated, contributing to improved path planning. A comparative analysis of computational complexity and execution time between the QSMSOR method and existing approaches demonstrates the superiority of red–black variants, particularly the QSMSOR method. Numerical experiments show that in various environments, the proposed method enables a mobile robot to navigate smoothly and efficiently toward a specific destination from any starting point.