(untitled) (Statistics, Optimization & Information Computing, 2025)
The main objective of the Mobile Robot Path Planning Problem is to find the optimal waypoints for a mobile robot with obstacles collision-free. This is a very complicated and needed task in robotic. Basically, planning rapidly the optimal task will increase the performance of the robot by increasing the speed to reach the target position and reducing energy conception. In this research work, the innovative technique namely Dhouib-Matrix-SPP (DM-SPP) is studied with eight movement directions as well as four. DM-SPP is a very rapid method built on the contingency matrix navigation and needing only n iterations to create the optimal path (where n is the number of nodes). The simulation results on several complicated case studies (varying from (20 x 20) grid map to (80 x 80) grid map) prove that DM-SPP can rapidly create an accurate trajectory with obstacles collision-free. Moreover, the proposed technique is compared with the very recently designed artificial intelligence approaches. The results of this comparison proved that the novel DM-SPP is the fastest approach: For example, it is (289.325) times rapider than the A* algorithm, (156.769) times faster than the Improved A* method, (127.901) times speedier than the Bidirectional A* technique, (69.586) times quicker than the Improved Bidirectional A* algorithm and (45.671) times rapider than the Variable Neighborhood Search BA* metaheuristic. These findings underline the speed of the proposed DM-SPP optimization technique and emerge the applicability of DM-SPP as a reliable option for the trajectory optimization.