Crates.io | bevy_flowfield_tiles_plugin |
lib.rs | bevy_flowfield_tiles_plugin |
version | 0.11.0 |
source | src |
created_at | 2023-07-24 20:34:50.016274 |
updated_at | 2024-10-02 23:41:58.229613 |
description | An implementation of FlowField (vector field) pathfinding as a plugin to the Bevy game engine |
homepage | https://github.com/BlondeBurrito/bevy_flowfield_tiles_plugin |
repository | https://github.com/BlondeBurrito/bevy_flowfield_tiles_plugin |
max_upload_size | |
id | 924938 |
size | 679,095 |
Inspired by the work of Elijah Emerson and with inspiration from leifnode and jdxdev this is an attempt to implement the data structures and logic required to generate a Flowfield representation of a world which can be used to pathfind movable actors.
bevy | bevy_flowfield_tiles_plugin |
---|---|
0.14 | 0.10 - 0.11 |
0.13 | 0.7 - 0.9 |
0.12 | 0.5 - 0.6 |
0.11 | 0.1 - 0.4 |
Pathfinding in games can take different forms and those forms have certain benefits aligned with the type of game they are being applied to. Generally people run across:
For larger and larger environemnts with an increasing number of pathing actors it may be beneficial to adopt a FlowField based approach due to the data sharing and formation/group like movement it promotes. FlowField Tiles are complex, it's effectively akin to fluid mechanics, so this is an attempt to bring an agnostic implementation to the Bevy game engine. My motivation for this is that I recently implemented a Way-point Graph for a prototype. In order to provide 'ok' actor movement it had to be made from 16 million data points. To prevent an actor from occasionally zig-zagging across the game world the granularity had to be boosted to 80 million data points to create a 'lifelike' impression of movement. That was just silly so I began looking into the history of pathfinding whereupon I stumbled across FlowField Tiles and decided to try and implement it with my favourite langauge and engine.
CostField
, IntegrationField
and FlowField
). A game world is effectively represented by a number of SectorsCostField
has one of theseFlowField
IntegrationField
which decribes how an actor should move (flow) across the worldFlowFields
allowing multiple actors to use and reuse themTo generate a set of navigation FlowFields
the game world is divided into Sectors indexed by (column, row)
and each Sector has 3 layers of data: [CostField, IntegrationField, Flowfield]
. Each layer aids the next in building out a path. A concept of Portals
is used to connect Sectors together.
For a 3-dimensional world the x-z
(x-y
in 2d) plane defines the number of Sectors used to represent it with a scale factor called sector_resolution
. This means that a for a (30, 30)
world with a resolution of 10
there would be 3x3
Sectors representing it - this implies that a single sector has relative dimensions of (10, 10)
and a single field cell within a sector represents a 1x1
unit area. Each Sector has an associated unqiue ID taken as its position: (column, row)
.
Likewise for a (300, 550)
resolution 10
world you'll be looking at 30
columns and 55
rows. The advantage of dividing a world into Sectors (as opposed to treating the whole world as a giant Flowfield
) is that the work in generating a path can be split into multiple operations and only touch certain sectors. Say for the (300, 550)
world you do treat it as a single set of fields - when calculating a path you could potentially have to calculate the Flowfield values for 165,000
field cells. Splitting it into sectors may mean that your path only takes you through 20 sectors, thereby only requiring 2,000
Flowfield
field cells to be calculated.
A CostField
is an MxN
2D array of 8-bit values, by default this is always a 10x10
array. The values indicate the cost
of navigating through that cell of the field. A value of 1
is the default and indicates the easiest cost
, and a value of 255
is a special value used to indicate that the field cell is impassable - this could be used to indicate a wall or obstacle. All other values from 2-254
represent increasing cost, for instance a slope or difficult terrain such as a marsh. The idea is that the pathfinding calculations will favour cells with a smaller value before any others.
At runtime the CostField
is generated for each Sector with the default value - although with the feature ron
it is possible to load the fields from disk, or with the feature heightmap
a greyscale png/jpeg can be used to seed the fields. See the Usage section below for details on updating the CostFields
during an inital pass (i.e when loading a level) and tweaking it during gameplay for a world which dynamically evolves with obstacles (flipping a cell to to a higher cost or an impassable 255
when something like a wall is placed or the ground splits into a fissure).
This array is used to generate the IntegrationField
when requesting a navigatable path.
Each Sector has up to 4 boundaries with neighbouring Sectors (fewer when the sector is in a corner or along the edge of the game world). Each boundary can contain Portals which indicate a navigatable point from the current Sector to a neighbour. Portals serve a dual purpose, one of which is to provide responsiveness - FlowFields
may take time to generate so when an actor needs to move a quick A* pathing query can produce an inital path route based on moving from one Portal to another and they can start moving in the general direction to the goal/target/endpoint. Once the FlowFields
have been built the actor can switch to using them for granular navigation instead.
The following sectors are located away from any edges of the world which means each boundary can have Portals (the purple cells):
A Portal is generated at the midpoint of a boundary - in situations where the CostField
contains 255
costs along the edge then multiple Portals may be generated at the midpoint of each valid pathable segment along the boundary and this is propagated to neighbouring Sectors so that every Portal has a neighbour buddy (as evident in the right hand Sector above, S(1, 1)
portal (9, 1)
allows movement into S(2, 1)
portal (0, 1)
, even though S(2, 1)
has a whole boundary that appears completely pathable).
On a larger scale (but still small) and for the simplist CostField
available, a 2x2
Sector grid produces predictable boundary Portals.
For finding a path from one Sector to another at a Portal level all Sector Portals are recorded within a data strucutre known as PortalGraph
. The Portals are stored as Nodes and Edges are created between them to represent traversable paths, it gets built in three stages:
node
edges
(pathable routes) to and from each Portal node
- effectively create internal walkable routes of each sectoredges
across the Portal node
on all sector boundaries (walkable route from one sector to another)This allows the graph to be queried with a source
sector and a target
sector and a list of Portals are returned which can be pathed. When a CostField
is changed this triggers the regeneration of the sector Portals for the region that CostField
resides in (and its neighbours to ensure homogenous boundaries) and the graph is updated with any new Portals nodes
and the old ones are removed.
An IntegrationField
is an MxN
2D array of 32-bit values. It uses the CostField
to produce a cumulative cost to reach the end goal/target. It's an ephemeral field, as in it gets built for a required sector and then consumed by the FlowField
calculation. The first 16-bits of each field cell value are used for a cost measurement while the second 16-bits are used as flags to indicate certain properties of a cell. The flags are classified as:
INT_BITS_WAVE_BLOCKED
When a new route needs to be processed the first 16-bits of the field values are set to u16::MAX
and the field cell containing the goal is set to 0
. Any cells which are impassable in the CostField
are marked in the IntegrationField
with their second 16-bits as INT_BITS_IMPASSABLE
.
The IntegrationField
is built from a number of passes:
A Portal represents the midpoint of a traversable sector boundary, when generating the field we expand the portals to cover their entire segment - this increases efficiency so that an actor can more directly approach its goal rather than zig-zagging to portal boundary points.
Note that portals are only expanded to field cells if they are pathable from both neighbouring sectors, a neighbour that has impassable cells will shorten the pathable segemnt.
In order to reduce needless pathfinding near the goal a Line Of Sight (LOS) pass is performed from the goal Sector. The idea being that if an actor moves into a field cell that has LOS then it no longer needs to follow the FlowFields and can instead directly path to the goal.
The LOS phase begins as a wavefront from the goal that interrogates the adjacent neighbouring field cells. If an adjacent cell is not marked as impasssable then it must have LOS to the goal and the value of the cell receives a wavefront cost plus the LOS bit flag. The wavefront then expands (whereby the wavefront cost increments by 1) to interrogate the adjacent cells of the neighbours and repeats until the wavefront cannot propagate any further.
As the wavefront expands it may encounter an impassable field cell (a block box in the diagrams). This causes two things to happen:
First, wavefront expansion cannot continue in the direction of the impassable field cell so it is removed from being a candidate in the next round of wavefront propagation.
Second, if there is a vacant field cell next to the impassable field cell then this indicates a Corner. A Corner means that LOS will be blocked in a given direction and the Corner is recorded for stage 3, the integrated cost calculation.
By taking a vector from the starting goal to the corner we can then extend this vector to calculate what field cells lie along a line. The field cells on this line are stored as corners and are updated with the flag for WavefrontBlocked. Meaning that as LOS expands and propagates if a WavefrontBlocked cell is encountered then the cell is removed as a candidate in further LOS porpagation. This ensures that LOS cannot flow around impassable areas.
Any available LOS propagation continues until all possible cells are exhausted:
Once the wavefront has exhausted expansion from either hitting the sector boundaries or from impassable cells/corners we can then calculate the actual integrated cost of the field.
From the Corners of an IntegrationField
recorded previously we start a new series of wavefronts that radiate from the corners considering any adjacent field cells that have not been marked as LOS or impassable.
To calculate the cost of the cells in the field:
CostField
valueCostField
cost to the IntegrationFields
cost of the current cell (at the corner the wavefront cost assigned was 4, assuming the CostField
value of the adjacent cell is 1
then the integrated cost becomes 5
)The end result effectively produces a gradient of high numbers to low numbers, a flow of sorts.
For Sectors other than the goal the process is effectively the same where boundary portals are treated as corners and wave propagation exapaned.
NB: the following diagrams use smaller sector sizes and exclude LOS but demonstrate how integrated cost is accumulated and creates a gradient from portal to portal
From the PortalGraph
we can get a path of Portals
to guide the actor over several sectors to the desired sector, the IntegrationField
of the goal sector has been calculated so next we "hop" through the boundary Portals
working backwards from the goal sector to the actor sector (Portals are denoted as a purple shade) to produce a series of IntegrationFields
for the chaining Sectors describing the flow movement.
In terms of pathfinding the actor will favour flowing "downhill". From the position of the actor and looking at its field cell neighbours a smalller value in that sectors IntegrationField
means a more favourable point for reaching the end goal, going from smaller to smaller values, basically a gradient flowing downhill to the destination.
This informs the basis of a FlowField
.
As an example for a 30x30
world (manually calculated), goal at 0
with an actor at A
, an IntegrationField
set interrogating all sector Portals
may produce a set of fields looking similar to:
Notice the cool waves that propagate out from the goal!
Generating the fields for this path programmatically leads to:
From the IntegrationFields
we can now build the final set of fields - FlowFields
A FlowField
is an MxN
2D array of 8-bit values built from a Sectors IntegrationField
. The first 4 bits of the value correspond to one of eight ordinal movement directions an actor can take (plus a zero vector when impassable) and the second 4 bits correspond to flags which should be used by a character controller/steering pipeline to follow a path.
The directional bits are defined as:
0b0000_0001
- North0b0000_0010
- East0b0000_0100
- South0b0000_1000
- West0b0000_0011
- North-East0b0000_0110
- South-East0b0000_1100
- South-West0b0000_1001
- North-West0b0000_0000
- zero vector, represents impassable cells0b0000_1111
- default on FlowField
initialisation, is always replaced by other valuesThe assistant flags are defined as:
0b0001_0000
- pathable0b0010_0000
- has line-of-sight to goal, an actor no longer needs to follow the field, it can move in a straight line to the goal. This avoids calculating field values that aren't actually needed and once an actor enters a cell with this flag then they no longer need to spend time looking up a `FlowField``0b0100_0000
- indicates the goal0b1000_0000
- indicates a portal goal leading to the next sectorSo a field cell in the FlowField
with a value of 0b0001_0110
means the actor should flow in the South-East direction. In terms of use don't worry about understanding these bit values too much, the Usage section shows the helpers for interpreting the values of the FlowField
to steer an actor.
Using the IntegrationFields
generated before, with an actor in the top right trying to reach the bottom left, we now generate the FlowFields
:
The thinner porition of each cell icon indicates the flow direction. The actor runs along the flow lines leading to the goal. This means for a group of actors they will flow towards the goal with a formation-like behaviour along the flow lines.
To enable actors to reuse FlowFields
(thus avoiding repeated calculations) a pair of caches are used to store pathing data:
Route Cache - when an actor requests to go somewhere a high-level route is generated from describing the overall series of sector-portals to traverse (PortalGraph
A*). If a FlowField
hasn't yet been calculated then an actor can use the route_cache
as a fallback to gain a generalist direction they should start moving in. Once the FlowFields
have been built they can swap over to using those more granular paths. TODO: Additionally changes to CostFields
can change portal positions and the real best path, so FlowFields
are regenerated for the relevant sectors that CostFields
have modified and during the regeneration steps an actor can once again use the high-level route as the fallback
Field Cache - for every sector-to-portal part of a route a FlowField
is built and stored in the cache. Actors can poll this cache to get the true flow direction to their goal. A Character Controller/Steering Pipeline is responsible for interpreting the values of the FlowField
to produce movement - while this plugin includes a Steering Pipeline the reality is that every game has it's own quirks and desires for movement so you will most likely want to build your own Pipeline. The real point of this plugin is to encapulsate the data structures and logic to make a FlowField
which an Actor can then read through it's own implementation.
Note that the data stored in the caches is timestamped - if a record lives longer than 15 minutes then it is purged to reduce size and improve lookup efficiency. When implemnting a steering pipeline/character controller to interpret the FlowFields
you may need to account for these old routes/paths expiring.
In a simulation you may have actors of different sizes and a gap between impassable walls, consider these purple actors:
The smaller actor on the left can evidently pass through the gap between the impassable terrain. On the right however the actor is much larger and as such when processing a PathRequest
only routes with suitable clearance should be considered (otherwise with a collision system in place it'd just bump into the walls to the side and never make it through).
To handle this the overall MapDimenions
component which defines the sizing of the various fields contains an actor_scale
parameter. This scaling is determined by the actor size and unit-size of a cell within a field. For instance a Sector with pixel dimensions of 640x640
means that each cell in the (m, n) -> (10, 10)
fields represents a pixel area of 64x64
, if an actor is larger than 64
pixels in width then a ratio between actor size and cell size is applied to 'grow' impassable cells to close off gaps that would be too small for the actor to path through.
In terms of what an actor 'sees' after requesting a route, the smaller actor on the left can path through the gap whereas the larger actor on the right would search for an alternate route:
In a game with actors of multiple sizes you will want to create distinct entities from FlowFieldTilesBundle
where each is configured to handle a certain size of actor.
#[derive(Component)]
struct ActorSmall
#[derive(Component)]
struct ActorLarge
fn setup () {
let map_length = 1920;
let map_depth = 1920;
let sector_resolution = 640;
let actor_size_small = 16.0;
cmds.spawn(FlowFieldTilesBundle::new(
map_length,
map_depth,
sector_resolution,
actor_size_small
)).insert(ActorSmall);
let actor_size_large = 78.0;
cmds.spawn(FlowFieldTilesBundle::new(
map_length,
map_depth,
sector_resolution,
actor_size_large
)).insert(ActorLarge);
}
fn system_navigation_small_actors(
actor_q: Query<&Actor, With<ActorSmall>>,
field_q: Query<&FlowCache, With<ActorSmall>>
) {/* handling movement etc */}
fn system_navigation_large_actors(
actor_q: Query<&Actor, With<ActorLarge>>,
field_q: Query<&FlowCache, With<ActorLarge>>
) {/* handling movement etc */}
Update your Cargo.toml
and add any features you require, to actually interface with calculated fields you should enable either 2d
or 3d
depending on the coordinate system of your world:
[dependencies]
bevy_flowfield_tiles_plugin = { version = "0.x", features = ["3d"] }
Add the plugin to your app:
use bevy_flowfield_tiles_plugin::prelude::*;
fn main() {
App::new()
// ... snip
.add_plugins(FlowFieldTilesPlugin)
// ... snip
}
In your own simulation you may well be using custom schedules or stages to control logic execution, the plugin as is sets all the logic to run as part of the PreUpdate
phase of the main Bevy schedule. To implement the logic into your own scheduling disect the contents of plugin/mod.rs
- note that certain systems have been chained
together and they must remain chained for accurate paths to be computed.
Next it's time to spawn the bundle entity configured to your world size (looking through the examples will give some pointers on this too).
The size and resolution of the world need to be known at initialisation and three values are required:
map_length
- in 2d this refers to the pixel x
size of the world. In 3d this is simply the x
sizemap_depth
- in 2d this refers to the pixel y
size of the world. In 3d this is the z
sizesector_resolution
- determines the numder of sectors by taking each size and dividing them by this value. In 2d this is basically the pixel length of each sector side and likewise for 3d it's the length of each sector side using whatever unit of measurement you've defined (for ease of use I go with a unit of x
is 1 meter and a unit of z
is one meter)
(1920, 1080)
with a resolution of 40
will produce 48x27 sectors. Another way of looking at this could be based on the idea of having a world made of sprites where each sprite corresponds to where a FieldCell
would be. If these regular sized sprites have a pixel length and height of 64
and your world is made from a 20x20
grid of these sprites then you can calcualte what the size is. map_length
would be your sprite length multiplied by the number sprites along the x
axis of the world, i.e 64 * 20 = 1280
. map_depth
follows a likewise calculation 64 * 20 = 1280
. As for resolution it will depend on how granular you want, in this example case a 10x10
CostField
is supposed to overlay an exact number of sprites so we use the sprite size to find the resolution 64 * 10 = 640
.(780x440)
with resolution 10
produces 78x44
sectors. Given that fields are 10x10
arrays this translates to a single FieldCell
representing a 1x1
unit areaWithin a system somewhere you can spawn the Bundle:
fn my_system(mut cmds: Commands) {
let map_length = 1920;
let map_depth = 1920;
let sector_resolution = 640;
let actor_size = 16.0;
cmds.spawn(FlowFieldTilesBundle::new(map_length, map_depth, sector_resolution, actor_size));
}
Note that this will initialise all the CostFields
representing the world with cell values of 1
. Meaning everywhere is pathable, in all likihood you'll then need to seed the fields with true values.
In 3d you could consider making a raycast to the centre of where each FieldCell would be and use something like the y
position of the ray hit to determine if something is passable or not and then flip the value of that particular FieldCell
(EventUpdateCostfieldsCell
can be used to queue a cost change).
Most likely for 2d or more complex 3d scenarios you'll probably want to enable either the ron
, csv
or heightmap
feature which allows for creating a FlowFieldTilesBundle
with inital CostFields
from a .ron
file, a collection of .csv
or a greyscale png/jpeg where pixel colour channels are translated into costs, the examples showcase this in more detail.
When it comes to interacting with the algorithm this is based on an event to be emitted when a movable actor needs a path:
struct EventPathRequest {
/// The starting sector of the request
source_sector: SectorID,
/// The starting field cell of the starting sector
source_field_cell: FieldCell,
/// The sector to try and find a path to
target_sector: SectorID,
/// The field cell in the target sector to find a path to
target_goal: FieldCell,
}
Each parameter can be determined by querying the MapDimension
component of the Bundle with the starting and end Transform::translation
of actor position and target position.
Using some example components to track and label an Actor:
/// Enables easy querying of Actor entities
#[derive(Component)]
struct Actor;
/// Consumed by an Actor steering pipeline to produce movement
#[derive(Default, Component)]
struct Pathing {
target_position: Option<Vec2>,
metadata: Option<RouteMetadata>,
portal_route: Option<Vec<(SectorID, FieldCell)>>,
has_los: bool,
}
We can then do something like process mouse clicks assign an actor a target_position
(in 3d use the methods ending in xyz instead):
fn user_input(
mouse_button_input: Res<ButtonInput<MouseButton>>,
windows: Query<&Window, With<PrimaryWindow>>,
camera_q: Query<(&Camera, &GlobalTransform)>,
dimensions_q: Query<&MapDimensions>,
mut actor_q: Query<&mut Pathing, With<Actor>>,
) {
if mouse_button_input.just_released(MouseButton::Right) {
// get 2d world positionn of cursor
let (camera, camera_transform) = camera_q.single();
let window = windows.single();
if let Some(world_position) = window
.cursor_position()
.and_then(|cursor| camera.viewport_to_world(camera_transform, cursor))
.map(|ray| ray.origin.truncate())
{
let map_dimensions = dimensions_q.get_single().unwrap();
if map_dimensions
.get_sector_and_field_cell_from_xy(world_position)
.is_some()
{
let mut pathing = actor_q.get_single_mut().unwrap();
// update the actor pathing
pathing.target_position = Some(world_position);
pathing.metadata = None;
pathing.portal_route = None;
pathing.has_los = false;
} else {
error!("Cursor out of bounds");
}
}
}
}
The actor can then query the RouteCache
to obtain a route - or if one doesn't exist it can emit a request to have a route generated.
fn get_or_request_route(
route_q: Query<(&RouteCache, &MapDimensions)>,
mut actor_q: Query<(&Transform, &mut Pathing), With<Actor>>,
mut event: EventWriter<EventPathRequest>,
) {
let (route_cahe, map_dimensions) = route_q.get_single().unwrap();
for (tform, mut pathing) in &mut actor_q {
if let Some(target) = pathing.target_position {
// actor has no route, look one up or request one
if pathing.portal_route.is_none() {
if let Some((source_sector, source_field)) =
map_dimensions.get_sector_and_field_cell_from_xy(tform.translation.truncate())
{
if let Some((target_sector, goal_id)) =
map_dimensions.get_sector_and_field_cell_from_xy(target)
{
// if a route is calculated get it
if let Some((metadata, route)) = route_cahe.get_route_with_metadata(
source_sector,
source_field,
target_sector,
goal_id,
) {
pathing.metadata = Some(*metadata);
pathing.portal_route = Some(route.clone());
} else {
// request a route
event.send(EventPathRequest::new(
source_sector,
source_field,
target_sector,
goal_id,
));
}
}
}
}
}
}
}
And once the FlowFields
have been built they can query the FlowFieldCache
instead and apply/queue up some kind of movement.
Note this example is very basic as it only handles a single actor, in an application you'd devise your own handling system:
const SPEED: f32 = 64.0;
fn actor_steering(
mut actor_q: Query<(&mut LinearVelocity, &mut Transform, &mut Pathing), With<Actor>>,
flow_cache_q: Query<(&FlowFieldCache, &MapDimensions)>,
time_step: Res<Time>,
) {
let (flow_cache, map_dimensions) = flow_cache_q.get_single().unwrap();
for (mut velocity, tform, mut pathing) in actor_q.iter_mut() {
// lookup the overarching route
if let Some(route) = pathing.portal_route.as_mut() {
// find the current actors postion in grid space
if let Some((curr_actor_sector, curr_actor_field_cell)) =
map_dimensions.get_sector_and_field_cell_from_xy(tform.translation.truncate())
{
// trim the actor stored route as it makes progress
// this ensures it doesn't use a previous goal from
// a sector it has already been through when it needs
// to pass through it again as part of a different part of the route
if let Some(f) = route.first() {
if curr_actor_sector != f.0 {
route.remove(0);
}
}
// lookup the relevant sector-goal of this sector
'routes: for (sector, goal) in route.iter() {
if *sector == curr_actor_sector {
// get the flow field
if let Some(field) = flow_cache.get_field(*sector, *goal) {
// based on actor field cell find the directional vector it should move in
let cell_value = field.get_field_cell_value(curr_actor_field_cell);
if has_line_of_sight(cell_value) {
pathing.has_los = true;
let dir =
pathing.target_position.unwrap() - tform.translation.truncate();
velocity.0 = dir.normalize() * SPEED * time_step.delta_seconds();
break 'routes;
}
let dir = get_2d_direction_unit_vector_from_bits(cell_value);
if dir.x == 0.0 && dir.y == 0.0 {
warn!("Stuck");
pathing.portal_route = None;
}
velocity.0 = dir * SPEED * time_step.delta_seconds();
}
break 'routes;
}
}
}
}
}
}
NB: generated FlowFields and Routes expire from their caches after 15 minutes, your steering pipeline may need to send a new EventPathRequest
if one gets expired that an actor was relying on.
NB: when a CostField is modified Portals and the PortalGraph are updated and any Routes or FlowFields involving the modified Sector CostField are removed - they will be regenerated but a CharacterController needs to be able to handle a route vanishing from the cache and then coming back (if it can come back, the CostField update may make a route invalid if a path no longer exists).
If you're combining this with a Physics simulation you'll need to ensure that your CharacterController is very robust, consider some scenarios that may happen:
serde
- enables serlialisation on some data typesron
- enables reading CostField
from files. NB: fixed-size arrays in .ron
are written as tuplescsv
- enables creating all of the CostFields
by reading from a directory of csv files. Note that csv filenames need to follow the sector ID convention of column_row.csv
, the underscore is important, and the path of the directory should be fully qualified and the files themselves should not contain any headers2d
- enables interface methods when working with Flowfields in a 2d world, additionally allows using a list of Bevy 2d meshes to initialise the Flowfields3d
- enables interface methods when working with FlowFields in a 3d worldheightmap
- allows initialising the CostField
s from a greyscale png/jpeg where each pixel of the image represents a FieldCell
. Alpha channel is optional (it'll just be ignored if included in the image). A pixel with colour channels (0, 0, 0, 255)
(black) represents an impassable 255
cost whereas (255, 255, 255, 255)
(white) is translated as a cost of 1
, channel values in between will be more expensive costsBenchmarks are split into two categories:
CostFields
Portals
across 100x100 sectorsPortalGraph
for 100x100 sectorsFlowFieldTilesBundle
readyFlowFields
describing movement across uniform CostFields
(cost = 1) from one corner to anotherFlowFields
describing movement across a variety of sectors containing clumps of impassable tilesFlowFields
describing movement from one corner to another in a 100x100 sector world. The world is composed of vertical corridors meaning that the actor has to path up and down to eventually snake it's way to the goalCurrently the slowest area is generating the PortalGraph
(7s on my machine) so this should be some initialisation that happens behind the scenes (like a loading screen or some such).
Depending on pathing complexity I've seen FlowField
generation range from 5-90ms.
Dual license of MIT and Apache.