Sep 20, 2025

Stingr Engine

Stingr Engine

v 0.0.01

Reflection, Proof of concept, better memory management

Core runtime

  • UE5-native C++ SDK — drop-in Unreal plugin; modular systems you can turn on/off per project.

  • Multithreaded by design — agent updates, queries, and tasks parallelized for modern CPUs.

  • Data-oriented architecture — cache-friendly containers, predictable memory, low allocator churn.

  • Deterministic step option — fixed-tick simulation for reproducible gameplay and networking.

Scale & performance

  • Large-crowd simulation — thousands to tens of thousands of agents at stable frame rates (exact numbers depend on content; reproducible benchmarks available on request).

  • Projection-based rendering — swap per-agent render modes at runtime (full Skeletal Mesh ↔ Instanced Skeletal Mesh ↔ lightweight impostors) based on LOD or budget.

  • Work budgeting — per-frame time budgets for AI/animation queries to keep frame times flat.

AI decision & behavior

  • Playbook/Blackboard runtime — lightweight decision layer with conditions, scoring, and gating.

  • Composable actions — define choices, sequences, and voting without tying logic to animation.

  • Dynamic evaluation rates — hot agents think more often; distant/idle agents cheap to maintain.

  • Perception hooks — LOS checks, proximity/area queries, and event-driven stimuli at scale.

Navigation & movement

  • Async pathfinding — background path requests with cancellation and smart replanning.

  • 3D/free-form locomotion — ground, air, and volume movement (XYZ), with accel/decel, pause/resume.

  • Crowd-aware steering — separation/alignment/cohesion (boids-style) and obstacle avoidance.

  • Navmesh integration — walkability checks, path corridor following, dynamic obstacle support.

Animation system

  • Instanced Skeletal Mesh (ISKM) — batch thousands of similar rigs with shared pose data.

  • Leader-pose sharing — followers derive transforms from a leader to minimize animation cost.

  • Blend & start-at controls — programmatic clips, loop/fade, and precise time offsets.

  • State-agnostic — animation is decoupled from decision logic (behaviors choose, anim plays).

Rendering & LOD

  • Runtime LOD policy — per-agent rules to switch render backends and animation detail.

  • Crowd culling — distance/angle/occlusion signals to thin out work before it hits the GPU.

  • Material/slot mapping — consistent skinning/material setups across render modes.

Spatial systems

  • Fast spatial hashing — constant-time neighborhood lookups for perception and steering.

  • Zone & interest management — subscribe agents to local regions to cut broadcast noise.


Make better experiences!

© All right reserved

Make better experiences!

© All right reserved

Make better experiences!

© All right reserved