bevy_northstar 0.2.0

A Bevy plugin for Hierarchical Pathfinding
Documentation

bevy_northstar

Crates.io docs license Crates.io Following released Bevy versions

A 2d/3d hierarchical pathfinding crate for Bevy.

bevy_northstar works by dividing the map into chunks and then calculates nodes based on the entrances between chunks. The nodes are used in pathfinding to get a higher level path that is significantly faster to calculate over long distances. Once the high level path is determined between a start and goal point it's refined to get a more accurate path. The crate provides:

Features

  • Supports 2D and 3D Tilemaps – Supports 2d and 3d tilemaps.

  • Optimized Performance – Algorithms are heavily benchmarked for efficiency.

  • Gizmo Debug View – Debug visuals for verifying the built HPA graph. Pathing debug components to visualize an entities path.

  • Stress Tests – 128x128 map with 128 entities to stress test HPA vs A* and collision. A collision example is provided to stress test narrow pathing.

  • Dynamic Collision & Avoidance – For moving colliders attaching a simple Blocking marker component is all that's needed. If you use the built in systems the pathing will do a configurable look ahead to see if it can do a fast local A* reroute.

  • Bevy Systems Integration – Bevy systems and components for pathfinding as well as collision markers when avoidance paths fail.

Demo

cargo run --example demo --features stats --release

Press P to switch between HPA* and traditional A* Press C to disable/enable collision

Screenshot 2025-03-30 at 9 34 05 AM

Documentation

  • API Reference on docs.rs
  • Usage guide and explanations in the book
  • Examples in the repository

Feature Flags

This crate has the following Cargo features:

  • stats: Enables pathfinding benchmarks. Useful to get an idea of how much time it's using per frame.

Quick Start

Add required dependencies to your Cargo.toml file:

[dependencies]
bevy = "0.16"
bevy_northstar = "0.2"

The basic requirements to use the crate are to spawn an entity with a Grid component, adjust the points, and then call Grid::build() so the chunk entrances and internal paths can be calculated.

To use the built-in pathfinding systems for the crate, insert the NorthstarPlugin specifying the Neighborhood to use.

The built-in neighborhoods are:

  • CardinalNeighborhood 4 directions allowing no diagonal movement.
  • CardinalNeighborhood3d 6 directions, including up and down, allowing no diagonal movement.
  • OrdinalNeighborhood 8 directions allowing for diagonal movement.
  • OrdinalNeighborhood3d 26 directions which includes the base ordinal movements and their up/down directions.
use bevy::prelude::*;
use bevy_northstar::prelude::*;

fn main() {
    App::new()
        .add_plugins(DefaultPlugins)
        // Add the Northstar Plugin with a selected neighborhood to use the built in pathfinding systems
        .add_plugins(NorthstarPlugin::<CardinalNeighborhood>::default())
        .add_systems(Startup, (startup, build_grid.after(startup)))
        .run();
}

fn startup(mut commands: Commands) {
    commands.spawn(Camera2d::default());

    // Spawn the grid used for pathfinding.
    commands.spawn(Grid::<CardinalNeighborhood>::new(&GridSettings {
        width: 16,
        height: 16,
        chunk_size: 4,
        ..Default::default()
    }));
}

fn build_grid(grid: Single<&mut Grid<CardinalNeighborhood>>) {
    let mut grid = grid.into_inner();

    // Let's set the position 8, 8 to a wall
    grid.set_point(UVec3::new(8, 8, 0), Point::new(u32::MAX, true));

    info!("Building the grid...");

    // The grid needs to be built after setting the points.
    // Building the grid will calculate the chunk entrances and cache internal paths.
    grid.build();

    info!("Grid built successfully!");
}

Bevy Compatibility

bevy bevy_northstar
0.16 0.2

Roadmap / TODO

  • Modify & Rebuild Grid Chunks Dynamically – Support updates to the grid after it’s been built.
  • Pseudo-3D Tilemap Support – Add support for features like stairs and ramps without full 3D calculations.
  • Parallelized Graph Building – Speed up grid/graph construction using parallelism.
  • Add Support For Multiple HPA Levels – Implement multiple hierarchical levels for improved efficiency.
  • Optimize 3D Performance – 3d grids appear to take a performance hit higher than expected currently.

Assets credits

Thanks

Thanks to the following crates and blogs that have been used as references