| Abstract [eng] |
Dynamic path finding algorithms combine heuristic and incremental search methods to solve a series of similar search tasks in both known and unknown environments. There are three classes of incremental search algorithms. In this document we provide a brief summary of dynamic path finding algorithms, that uses incremental search methods, but its main focus is on comparing main algorithms of all three incremental classes, that are guaranteed to give optimal solution in environment where action costs can increase and decrease over time, and showing their strong and weak sides. The algorithms are compared in three different situations: stationary, goal – directed and moving – target. At the end of the document conclusions are given based on performed work. In this paper, research showed that A* and FSA* are ~23,6% more efficient than GAA* and third incremental class algorithms when the amount of untraversable cells is ~16000 and ~42,3% more efficient when the amount of traversability changing cells is ~8000. When the amount of untraversable cells is between 1000 and 16000, the third incremental class algorithms are ~58,7% more efficient than GAA* and ~54% – than A* and FSA*. When the amount of traversability changing cells is between 500 and 8000, the third incremental class algorithms are ~69,3% more efficient than GAA* and ~47,8% – than A* and FSA*. |
