Abstract

In this paper, we explore the practical implications of our research, offering significant advantages to the autonomous and robotics sector. Our focus revolves around enhancing geometric path planning for mobile robots, a pivotal aspect of automation. Notably, we not only delve into how to formulate optimal navigation problems while considering practical constraints and applications, but we also introduce a novel Smoothed PSO-IPF algorithm. This algorithm serves as an illustrative example of an innovative and context-specific approach to addressing navigation challenges. It furnishes engineers and practitioners in the field with a comprehensive framework for designing navigational solutions. By presenting the PSO-IPF method as a hybrid approach, we effectively bridge the gap between classical and reactive methods. Consequently, it leads to enhanced navigation efficiency, reduced collisions, and heightened mobile robot reliability. This innovation not only optimizes navigation issues but also underscores its potential for diverse applications across various industries.