ROBOT_INSTANCING_README.md

Robot Instancing Optimization

This implementation optimizes the rendering of multiple robots using Threlte's instancing capabilities for improved performance.

Key Features

1. Smart Instancing by Robot Type

• Robots are grouped by their URDF type (URL) for optimal instancing
• Single robots render with full detail
• Multiple robots of the same type use instanced rendering

2. Geometry-Specific Instancing

• Box Geometries: Instanced with T.boxGeometry
• Cylinder Geometries: Instanced with T.cylinderGeometry
• Mesh Geometries: Instanced with simplified T.sphereGeometry for performance

3. Hybrid Rendering Strategy

• First robot of each type: Full detailed rendering with all URDF components
• Additional robots: Simplified instanced representation
• Maintains visual quality while optimizing performance

4. Performance Benefits

• Reduces draw calls when rendering multiple robots
• Optimizes GPU memory usage through instancing
• Scales better with increasing robot count
• Maintains interactivity for detailed robots

Implementation Details

State Management

// Robots grouped by URDF type for optimal batching
let robotsByType: Record<string, Array<{ 
  id: string; 
  position: [number, number, number]; 
  robotState: RobotState 
}>> = $state({});

Instancing Logic

1. Single Robot: Full UrdfLink rendering with all details
2. Multiple Robots:
   • Geometry analysis and grouping
   • Instanced rendering for primitive shapes
   • Simplified representations for complex meshes

Automatic Demonstration

• Spawns additional robots after 2 seconds to showcase instancing
• Shows performance difference between single and multiple robot rendering

Usage

Simply use the Robot.svelte component with a urdfConfig. The component automatically:

• Detects when multiple robots of the same type exist
• Switches to instanced rendering for optimal performance
• Maintains full detail for single robots

<Robot {urdfConfig} />

Performance Impact

• Before: O(n) draw calls for n robots
• After: O(1) draw calls per geometry type regardless of robot count
• Memory: Shared geometry instances reduce GPU memory usage
• Scalability: Linear performance improvement with robot count

This optimization is particularly beneficial for:

• Robot swarms
• Multi-robot simulations
• Arena scenarios with many similar robots
• Performance-critical real-time applications