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bevy-navigation

Bevy ECS skill for navigation. Keywords: Bevy, navigation, pathfinding, ECS.

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  • SKILL.md9.7 KB
  • references/ecs-ownership.md529 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

Bevy navigation

When to use

Load this when agents need a path over walkable space before adding a crate. Movement of the actor after a path exists belongs on bevy-character-movement. Policy for chase, patrol, and retarget belongs on bevy-ai-navigation.

ECS shape

  • Components store the goal cell and the waypoint list for one agent.
  • Resources own the walk grid: width, height, and blocked cells.
  • Systems search on Update, then step along the path on FixedUpdate. .chain() keeps the new path visible before motion.
  • Schedule: search and follow stay on the app schedules above. Crowd policy stays on bevy-ai-navigation.

Ownership

NeedBevy shape
AgentAn entity with a goal and a waypoint list
Walkable spaceA WalkGrid resource of blocked cells
AvoidanceSeparation stays on bevy-ai-navigation
Next waypointAgentPath stepped on FixedUpdate

Scope

  • A grid, a breadth-first search, and a follower are enough for walkable cells. Navmesh baking and crowd radius stay outside this skill.
  • Actor locomotion after a waypoint exists belongs on bevy-character-movement.

Examples

[package]
name = "navigation"
version = "0.1.0"
edition = "2021"

[dependencies]
bevy = "0.20"

The grid is a resource. Search writes waypoints. The follower consumes them on the fixed step.

use std::collections::VecDeque;

#[derive(Resource)]
struct WalkGrid {
    width: i32,
    height: i32,
    cell: f32,
    blocked: Vec<bool>,
}

#[derive(Component)]
struct GoalCell(i32, i32);

#[derive(Component)]
struct AgentPath {
    waypoints: Vec<Vec3>,
    index: usize,
}

fn cell_index(grid: &WalkGrid, x: i32, y: i32) -> Option<usize> {
    if x < 0 || y < 0 || x >= grid.width || y >= grid.height {
        return None;
    }
    Some((y * grid.width + x) as usize)
}

fn search(grid: &WalkGrid, start: (i32, i32), goal: (i32, i32)) -> Vec<Vec3> {
    let Some(start_i) = cell_index(grid, start.0, start.1) else {
        return Vec::new();
    };
    if grid.blocked[start_i] {
        return Vec::new();
    }
    let mut prev: Vec<Option<(i32, i32)>> = vec![None; grid.blocked.len()];
    let mut queue = VecDeque::new();
    prev[start_i] = Some(start);
    queue.push_back(start);
    while let Some((x, y)) = queue.pop_front() {
        if (x, y) == goal {
            break;
        }
        for (nx, ny) in [(x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)] {
            let Some(i) = cell_index(grid, nx, ny) else {
                continue;
            };
            if grid.blocked[i] || prev[i].is_some() {
                continue;
            }
            prev[i] = Some((x, y));
            queue.push_back((nx, ny));
        }
    }
    let Some(_) = cell_index(grid, goal.0, goal.1).filter(|i| prev[*i].is_some()) else {
        return Vec::new();
    };
    let mut cells = Vec::new();
    let mut cursor = goal;
    cells.push(cursor);
    while cursor != start {
        let Some(i) = cell_index(grid, cursor.0, cursor.1) else {
            break;
        };
        let Some(parent) = prev[i] else {
            break;
        };
        if parent == cursor {
            break;
        }
        cursor = parent;
        cells.push(cursor);
    }
    cells.reverse();
    cells
        .into_iter()
        .map(|(x, y)| Vec3::new(x as f32 * grid.cell, 0.0, y as f32 * grid.cell))
        .collect()
}

fn plan_paths(
    grid: Res<WalkGrid>,
    mut agents: Query<(&Transform, Ref<GoalCell>, &mut AgentPath)>,
) {
    let grid_changed = grid.is_changed();
    for (tf, goal, mut path) in &mut agents {
        if !grid_changed && !goal.is_changed() {
            continue;
        }
        let start = (
            (tf.translation.x / grid.cell).floor() as i32,
            (tf.translation.z / grid.cell).floor() as i32,
        );
        path.waypoints = search(&grid, start, (goal.0, goal.1));
        path.index = 0;
    }
}

fn follow_paths(time: Res<Time<Fixed>>, mut agents: Query<(&mut Transform, &mut AgentPath)>) {
    let step = 4.0 * time.delta_secs();
    for (mut tf, mut path) in &mut agents {
        let Some(goal) = path.waypoints.get(path.index).copied() else {
            continue;
        };
        let delta = goal - tf.translation;
        let dist = delta.length();
        if dist <= step || dist == 0.0 {
            tf.translation = goal;
            path.index += 1;
        } else {
            tf.translation += delta / dist * step;
        }
    }
}

pub struct NavigationPlugin;

impl Plugin for NavigationPlugin {
    fn build(&self, app: &mut App) {
        let width = 8;
        let height = 8;
        app.insert_resource(WalkGrid {
            width,
            height,
            cell: 1.0,
            blocked: vec![false; (width * height) as usize],
        })
        .add_systems(Update, plan_paths)
        .add_systems(FixedUpdate, follow_paths);
    }
}

Mark a cell blocked and give an agent a goal. Planning runs again because the grid resource changed.

#[derive(Resource)]
struct WalkGrid {
    width: i32,
    height: i32,
    cell: f32,
    blocked: Vec<bool>,
}

#[derive(Component)]
struct GoalCell(i32, i32);

#[derive(Component)]
struct AgentPath {
    waypoints: Vec<Vec3>,
    index: usize,
}

fn block_cell(mut grid: ResMut<WalkGrid>) {
    let x = 2;
    let y = 3;
    let i = (y * grid.width + x) as usize;
    if let Some(cell) = grid.blocked.get_mut(i) {
        *cell = true;
    }
}

fn spawn_agent(mut commands: Commands) {
    commands.spawn((
        Transform::from_xyz(0.0, 0.0, 0.0),
        GoalCell(5, 5),
        AgentPath {
            waypoints: Vec::new(),
            index: 0,
        },
    ));
}

Expert Knowledge Delta

Target: Bevy 0.20+.

Core ECS types: Component, Resource, Query, Commands, Startup, Update, Fixed / FixedMain (bevy::time), .chain(), Plugin, DefaultPlugins, MinimalPlugins. Messages and observers are an ownership slot. See bevy-events-messaging for their APIs. Systems run in parallel unless .chain() orders the ones that conflict.

Who owns state

PieceOwnerWho may mutateSchedule
Data on one entityComponentOne system via QueryUpdate or FixedMain
One value for the whole appResourceOne systemStartup to insert, then the schedule that reads it
SpawnCommandsThe spawning systemStartup for the initial world; later schedules for runtime spawn
Order that must not race.chain()The chained systems onlySame schedule
Plugin boundaryPluginbuild registers systems and resourcesBefore the app runs

Borrow rule: two systems that both mutably query the same component must be ordered (.chain()) or split so only one writes. Unrelated systems stay parallel. That is the ECS page rule, not a guess at a system-set API.

Decision

If you needDo thisDo not
Per-entity dataComponent + QueryA field stored outside a component
App-wide config or clockResourceCopy the value onto every entity
Stable simulation stepFixedMain and the Fixed clockTie simulation to raw frame Update
Startup spawnCommands in StartupSpawn from a render system
Cross-system notice that is not shared stateMessage or observer slot in bevy-events-messagingA new event type invented in this file
A path over cellsWalkGrid plus breadth-first searchAn engine navmesh type this crate does not ship

Load references/ecs-ownership.md for the ownership table.

NEVER

  • Do not pin /0.20.0/ in docs URLs. WHY: links stay on latest; the 0.20 target is stated once in prose.

  • Do not mutably query the same component from two unordered systems. WHY: the schedule runs systems in parallel unless .chain() orders them.

  • Do not invent a physics, navigation, networking, or XR crate here. WHY: this skill only names documented Bevy crates and modules.

  • No navigation types from another engine. WHY: Bevy code stays idiomatic ECS and uses only documented Bevy APIs.

  • No named third-party navigation crate as the chosen solver. WHY: Bevy code stays idiomatic ECS and uses only documented Bevy APIs.

  • No invented bake, avoidance, or path-query APIs. WHY: Bevy code stays idiomatic ECS and uses only documented Bevy APIs.

Reference

Official links stay on bevy.org. The library pin on bevy-master stays 0.20. No navigation module was opened.

Official Documentation

  • Assets - Official asset catalog. No navigation plugin was selected.
  • Examples - Example tree on the latest branch.
  • ECS - Component, Query, Commands, and .chain().
  • Quick Start: plugins - add_plugins without a chosen nav crate.

Related Skills

Prerequisites

Complements

Downstream / consumers

  • Genre skills route chase, patrol, and similar policies.

Master

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