Resumen
Graph search algorithms and shortest path algorithms, designed to allow real mobile robots to search unknown environments, are typically run in a hybrid manner, which results in the fast exploration of an entire environment using the shortest path. In this study, a mobile robot explored an unknown environment using separate depth-first search (DFS) and breadth-first search (BFS) algorithms. Afterward, developed DFS + Dijkstra and BFS + Dijkstra algorithms were run for the same environment. It was observed that the newly developed hybrid algorithm performed the identification using less distance. In experimental studies with real robots, progression with DFS for the first-time discovery of an unknown environment is very efficient for detecting boundaries. After finding the last point with DFS, the shortest route was found with Dijkstra for the robot to reach the previous node. In defining a robot that works in a real environment using DFS algorithm for movement in unknown environments and Dijkstra algorithm in returning, time and path are shortened. The same situation was tested with BFS and the results were examined. However, DFS + Dijkstra was found to be the best algorithm in field scanning with real robots. With the hybrid algorithm developed, it is possible to scan the area with real autonomous robots in a shorter time. In this study, field scanning was optimized using hybrid algorithms known.