Graph Search Techniques for Mobile Robot Path Planning

In a number of applications, the problem of determining the optimum path occurs. This applications range from finding the fastest path in a network, to determining the safest path for mobile vehicle, wandering on the surface of Mars. In this context, we shall limit our scope to the case of finding paths in Euclidean two-dimensional space. Moreover we shall limit the case study to movements along a surface that can be projected onto a directed graph. To be specific, we shall look at the case of finding the optimum path for a mobile robot moving along a flat surface, the robot’s configurations in the configuration space being the graph’s nodes while the graph’s arcs represent the cost of moving from one configuration to another. Researchers have tried to come with new and better navigation technologies in the last years. With the development of path finding, several new classical routing algorithms have been introduced to generate better routing solution. For example the Dijkstra algorithm is the most famous one, which evaluates the moving cost from one node to any other node and sets the shortest moving cost as the connecting cost of two nodes (Eklund et al., 1996). Around the same period of time, Best-First-Search algorithm is also introduced in the researchers’ community. A little different from the Dijkstra algorithm, Best-First-Search algorithm has a different approach because it estimates the distance from current position to goal position, and it chooses the step that is closer to the goal position (LaValle, 2006). The difficulty was growing with the new path finding situations so the old path finding algorithm had to be improved to meet the new introduced requirements. A new path finding algorithm was introduced and it was named the A* algorithm. The A* algorithm tries to combine the advantages offered by Dijkstra algorithm and Best-FirstSearch algorithm. This paper presents tests performed with various implementations of graph search algorithms (A*, D*, focused D*) as path planners for a mobile robot, focused on strong points and drawbacks of each implementation. 8