Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/4078 2018 2018 College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq Mohammed Mohammed Computer Science Department, University of Al-Maarif, Ramadi, Anbar, Iraq Mahmood Abdulrazzaq Alsaadi College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq Ruqayah R. Al Al-Dahhan College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq Salah A. .. Senior SoC Debug Engineer/Tech lead; intel corporation, USA Omar Q. Mohsin To facilitate the practical deployment of robotics, efficient path planning is essential to ensure that robotic movement is accurate, safe, and goal-oriented. This study explores new approaches to map adaptation and path optimization for robot navigation between specified locations. The initial phase of the research involves designing an environment that enables the safe operation of robots. Subsequently, the collected data is processed to construct a graph using Dijkstra’s algorithm, which is employed to determine the shortest path between key points. When multiple paths are available, the algorithm selects the most efficient one, while ensuring safety in point-to-point transitions and when navigating around obstacles. In addition to this, a reinforced method is introduced to enhance the security of path planning. This approach expands the original trajectory to incorporate a safety buffer equal to half of the robot’s safety radius, thus maintaining a safe distance along the traveled route. The key contribution of this work lies in the development of novel maps featuring secure pathways, which can be utilized by optimization algorithms to improve navigation in unfamiliar terrains. Experimental results using PRM* and RRT* validate the accuracy of these maps, especially in complex, maze-like environments. 2026 2026 199 210 10.54216/FPA.210213 https://www.americaspg.com/articleinfo/3/show/4078