This research aims to delve into the comparative analysis of two prominent path planning algorithms, Rapidly Exploring Random Trees (RRT) and A*, in the context of path planning within both 2D and 3D spaces using MATLAB. The study evaluates their performance metrics, such as processing time and path length, and emphasizes their adaptability to the intricacies of 3D environments. The investigation extends to practical considerations, representing the map as a simulated manufacturing environment, complete with fixed equipment and clutter. By implementing the algorithms in MATLAB, the study ensures a comprehensive examination, shedding light on the algorithms’ behavior and efficiency. Through this exploration, the research aims to provide valuable insights for decision-makers and researchers working on path planning applications in various real-world scenarios, with implications for unmanned aerial vehicle (UAV) in 3D spaces. The simulation results indicate a contrast between the RRT and A* algorithms. The RRT algorithm exhibits superior search speed but limitations in distance optimization compared to the A* algorithm.