Replaces the existing bi-directional search between points used by the pathfinder with a guided hierarchical search. The old search was a standard A* search with a heuristic of advancing in straight line towards the target. This heuristic performs well if a mostly direct path to the target exists, it performs poorly it the path has to navigate around blockages in the terrain. The hierarchical path finder maintains a simplified, abstract graph. When a path search is performed it uses this abstract graph to inform the heuristic. Instead of moving blindly towards the target, it will instead steer around major obstacles, almost as if it had been provided a map which ensures it can move in roughly the right direction. This allows it to explore less of the area overall, improving performance.
When a path needs to steer around terrain on the map, the hierarchical path finder is able to greatly improve on the previous performance. When a path is able to proceed in a straight line, no performance benefit will be seen. If the path needs to steer around actors on the map instead of terrain (e.g. trees, buildings, units) then the same poor pathfinding performance as before will be observed.
Two different issues were causing a path search to not explore cells in order of the cheapest estimated route first. This meant the search could sometimes miss a cheaper route and return a suboptimal path.
- PriorityQueue had a bug which would cause it to not check some elements when restoring the heap property of its internal data structure. Failing to do this would invalidate the heap property, meaning it would not longer return the items in correct priority order. Additional tests ensure this is covered.
- When a path search encountered the same cell again with a lower cost, it would not update the priority queue with the new cost. This meant the cell was not explored early enough as it was in the queue with its original, higher cost. Exploring other paths might close off surrounding cells, preventing the cell with the lower cost from progressing. Instead we now add a duplicate with the lower cost to ensure it gets explored at the right time. We remove the duplicate with the higher cost in CanExpand by checking for already Closed cells.
