Realistic Orbital Physics
An Unreal Engine 5 plugin that simulates realistic n-body gravitational physics and enables procedural generation of stable planetary systems. Built for performance, extensibility, and ease of use.
Overview
This plugin was born from a simple question: how do you simulate thousands of gravitating bodies in real-time without melting the CPU? The answer required rethinking how gravity calculations are typically handled in game engines, and building a system that's both physically accurate and performant enough for gameplay.
The plugin provides two core features: realistic n-body gravitational simulation and procedural generation of stable planetary systems. It's designed to be drag-and-drop for designers while exposing full control for programmers who need it.
Technical Challenges
1. N-Body Performance at Scale
The naive approach to n-body simulation is O(n²)—every body calculates attraction to every other body. At 100 bodies, that's 10,000 calculations per frame. At 1,000 bodies, it's a million. This doesn't scale.
I implemented a spatial partitioning system that groups distant bodies into aggregate masses, reducing complexity while maintaining accuracy for nearby interactions. Bodies within a threshold distance get full pairwise calculations; everything else uses approximations that are indistinguishable at gameplay scale.
2. Stable Orbit Generation
Procedurally generating planetary systems that don't immediately collapse or eject planets is harder than it sounds. You can't just place bodies randomly and hope for the best.
The generator uses Keplerian orbital mechanics to calculate initial velocities that produce stable orbits, with configurable eccentricity and inclination ranges. It also validates configurations against known instability patterns—no two planets in resonant orbits that would destabilize over time.
3. Trajectory Prediction
For gameplay purposes (spacecraft navigation, targeting), players need to see where bodies will be in the future. This means running the simulation forward without affecting the actual game state.
I built a prediction system that clones the simulation state and runs it forward on a separate thread, returning trajectory data that can be visualized as orbital paths. The system balances prediction accuracy against computational cost, with configurable time horizons and step sizes.
Systems Implemented
- World Subsystem — Central manager for all gravitating bodies, handles registration, updates, and spatial partitioning
- Gravity Component — Attachable to any actor, configures mass, collision behavior, and simulation parameters
- Orbit Predictor — Asynchronous trajectory calculation with LOD-based precision
- Procedural Generator — Stable system generation with customizable parameters for planet count, spacing, and orbital characteristics
- Spacecraft Controller — Pre-built actor component for player-controlled vehicles with realistic thrust and orbital maneuvering
- Debug Visualizer — Runtime visualization of gravity fields, orbital paths, and system stability metrics
Architecture Decisions
The plugin uses Unreal's Subsystem pattern for the core simulation, ensuring automatic lifecycle management and easy access from anywhere in the codebase. All heavy calculations run on game thread but are designed to be parallelizable for future optimization.
I chose to make the system Blueprint-friendly from day one. Every parameter is exposed, every event is broadcastable, and common operations have dedicated nodes. This wasn't just for accessibility—it forced me to design cleaner interfaces than I might have otherwise.
Outcomes & Learnings
The plugin handles 1,000+ simultaneous bodies at playable framerates on mid-range hardware. It's been used in space exploration prototypes, educational simulations, and a few projects I can't talk about yet.
Key lessons from this project:
- Profile early, optimize late — I spent too long optimizing code paths that turned out not to be bottlenecks
- Documentation is a feature — The projects that adopted this plugin fastest were the ones where I'd written thorough docs
- Test at scale from day one — Edge cases at 10 bodies become showstoppers at 1,000
Future Improvements
If I revisit this project, I'd like to add GPU-accelerated calculations for truly massive simulations (10,000+ bodies), multiplayer synchronization for the simulation state, and better tooling for designers to visualize system stability before committing to a configuration.