How can I optimize Astar for vast empty spaces? - c++

Question

I am creating a game with a 3D grid for flying entities, So I have a lot of points and connections in the air where there aren't any obstructions. I didn't want to decrease the resolution of my grid so I thought I could just skip over chunks (or empties as I call them) of the Astar map while they're not containing any obstructions, and I modified Godot's Astar algorithm to do this.
Unfortunately this ended up being slower than looping through points one at a time due to the way I implemented this modification, which needs to loop through all the edge points of an empty.
2D representation of how one edge point of an empty connects to all other edge points:
This ends up looping through a larger number of points than letting the A* algorithm work it's way through the empty.
So I'm sorta stumped on how to make this more efficient while still preserving the most optimal path.
I could potentially narrow down what faces of the empty should be scanned over by first comparing the center points of all 8 faces of the empty (as my grid consists of hexagonal prisms). Or maybe I should somehow use the face center points of the empty's faces exclusively instead of all edge points.
I mainly want to know if anyone has worked on an issue like this before, and if so what would be the recommended solution?
Here is the astar loop for reference:
bool AStar::_solve(Point *begin_point, Point *end_point, int relevant_layers) {
pass++;
//make sure parallel layers are supported
// or if *relevant_layers is 0 then use all points
bool supported = relevant_layers == 0 || (relevant_layers & end_point->parallel_support_layers) > 0;
if (!end_point->enabled || !supported) {
return false;
}
bool found_route = false;
Vector<Point *> open_list;
SortArray<Point *, SortPoints> sorter;
begin_point->g_score = 0;
begin_point->f_score = _estimate_cost(begin_point->id, end_point->id);
open_list.push_back(begin_point);
while (!open_list.empty()) {
Point *p = open_list[0]; // The currently processed point
if (p == end_point) {
found_route = true;
break;
}
sorter.pop_heap(0, open_list.size(), open_list.ptrw()); // Remove the current point from the open list
open_list.remove(open_list.size() - 1);
p->closed_pass = pass; // Mark the point as closed
//if the point is part of an empty, look through all of the edge points of said empty (as to skip over any points within the empty).
OAHashMap<int, Point*> connections;
PoolVector<Empty*> enabled_empties;
int size = p->empties.size();
PoolVector<Empty*>::Read r = p->empties.read();
for (int i = 0; i < size; i++) {
Empty* e = r[i];
supported = relevant_layers == 0 || (relevant_layers & e->parallel_support_layers) > 0;
//if the empty is enabled and the end point is not within the empty
if (e->enabled && supported && !end_point->empties.has(e)) {
enabled_empties.append(e);
//can travel to any edge point
for (OAHashMap<int, Point*>::Iterator it = e->edge_points.iter(); it.valid; it = e->edge_points.next_iter(it)) {
int id = *it.key;
Point* ep = *(it.value);
ep->is_neighbour = false;
//don't connect to the same point
if (id != p->id && (i == 0 || !connections.has(id))) {
connections.set(id, ep);
}
}
}
}
//add neighbours to connections
for (OAHashMap<int, Point*>::Iterator it = p->neighbours.iter(); it.valid; it = p->neighbours.next_iter(it)) {
int id = *it.key;
Point* np = *(it.value);// The neighbour point
np->is_neighbour = true;
//don't need to check for duplicate point connections if no empties
if (size == 0 || !connections.has(id)) {
//don't add points within enabled empties since they're meant to be skipped over
if (np->empties.size() > 0 && !np->on_empty_edge) {
bool in_enabled_empty = false;
PoolVector<Empty*>::Read r1 = np->empties.read();
for (int i = 0; i < np->empties.size(); i++) {
if (enabled_empties.has(r1[i])) {
in_enabled_empty = true;
break;
}
}
if (!in_enabled_empty) {
connections.set(id, np);
}
}
else {
connections.set(id, np);
}
}
}
for (OAHashMap<int, Point *>::Iterator it = connections.iter(); it.valid; it = connections.next_iter(it)) {
Point *e = *(it.value); // The neighbour point
//make sure parallel layers are supported
// or if *relevant_layers is 0 then use all points
supported = relevant_layers == 0 || (relevant_layers & e->parallel_support_layers) > 0;
if (!e->enabled || e->closed_pass == pass || !supported) {
continue;
}
real_t tentative_g_score = p->g_score + _compute_cost(p->id, e->id) * e->weight_scale;
bool new_point = false;
if (e->open_pass != pass) { // The point wasn't inside the open list.
e->open_pass = pass;
open_list.push_back(e);
new_point = true;
} else if (tentative_g_score >= e->g_score) { // The new path is worse than the previous.
continue;
}
e->prev_point = p;
e->prev_point_connected = e->is_neighbour;
e->g_score = tentative_g_score;
e->f_score = e->g_score + _estimate_cost(e->id, end_point->id);
if (new_point) { // The position of the new points is already known.
sorter.push_heap(0, open_list.size() - 1, 0, e, open_list.ptrw());
} else {
sorter.push_heap(0, open_list.find(e), 0, e, open_list.ptrw());
}
}
}
return found_route;
}
Note: I'm still not exactly sure what the sorter does.
the entire code can be seen here in a_star.cpp and a_star.h
Edit:
if anyone wants to reference or use this, I've modified the Astar code to add user-defined octants and to use a user-defined straight line function (they are user-defined so they can work with any type of grid) to be used between octants when possible to further decrease runtime, and it works very well in terms of speed. Though the pathing is not optimal, especially when adding a lot of obstacles/restricting the available positions.