Thanks to technological advances, mobile robots are no longer limited to their immediate environment and can move within a delimited or open space. Route planning for these robots is crucial, especially in storing volatile explosive materials. Starting from an initial dynamic configuration, possible movements and their limitations are determined based on the number and position of the robot’s wheels. In the military, mobile robotics is essential for safely and efficiently handling explosive materials. Robots can be programmed to follow specific routes, avoiding hazardous areas and minimizing risks. Path planning algorithms, such as Dijkstra and A-Star, calculate the best route from the starting point to the destination, ensuring that the robot avoids collisions and follows the optimal path. Dijkstra focuses on finding the shortest route through iterations, while A-Star uses a heuristic cost function for each explored node. MATLAB and Simulink allow for the development of scalable simulations to validate the performance of robots, facilitating the creation of prototypes and the evaluation of conceptual models. Efficient route planning improves the performance and safety of robots in industrial, logistical, and service applications.