Comparative Analysis among Categorical Shortest Path-finding Algorithms using OPSimDAZ

Efficient navigation of mobile robots is crucial for industrial applications. However, environmental obstacles can pose significant risks and hinder operational optimality. Thus, identifying the ideal algorithm through comparative analysis is imperative. This study examines five popular path planning algorithms; Dijkstra, BFS, A*, D* Lite, and Ant Colony Optimization (ACO); based on 2D grid simulation. The objective is to conduct performance analysis of these algorithms through a custom designed online simulation platform for visualization of path planning strategies. The methodology encompasses a thorough background study, environment setup, development of simulation platform, algorithm implementation, and result analysis with visualization. This study contributes by introducing a new simulation platform, and adding values to the existing knowledge of path planning analysis.