/** * SyntheticWalkCycleEngine — procedural walk-cycle implementation of MotionMatchingEngine. * * NOT a neural network. NOT trained. Hand-crafted sin-wave biped gait that * produces a deterministic, license-clean walk cycle. Useful as: * - Testing fixture for the runtime wrapper (visible motion in unit tests * without needing trained weights or a real ONNX backend). * - License-clean training-data generator — emits TrainingFrames that the * real BUILD-1 NN can learn from (procedural-to-neural distillation). * - Studio demo content while the real engine is in development. * * Explicitly NOT a substitute for the real neural inference (BUILD-1 * follow-up per /founder ruling 2026-04-26 — primary-literature * reimplementation). Named "synthetic" so the trait surface stays honest: * a future @stub-audit run that finds this engine knows it's intentional * scaffolding, not a stubbed-real-thing. */ import { type MotionInferenceInput, type MotionInferenceResult, type MotionMatchingEngine } from './motion-matching'; /** Joint names this engine drives — matches a generic biped rig. */ export declare const SYNTHETIC_WALK_JOINTS: readonly ["hip", "left_thigh", "right_thigh", "left_knee", "right_knee", "left_foot", "right_foot"]; /** * Build a biped pose at a given phase + speed. Pure function — same inputs * always produce the same pose. No timestamp in the joint values themselves * (timestamp is set by the engine on the SkeletonPose wrapper). */ export declare function buildSyntheticBipedPose(phase: number, speed: number): Record; export declare class SyntheticWalkCycleEngine implements MotionMatchingEngine { readonly modelId: string; loaded: boolean; constructor(modelId?: string); load(): Promise; infer(input: MotionInferenceInput): MotionInferenceResult; dispose(): void; } export declare function createSyntheticWalkCycleEngine(modelId?: string): MotionMatchingEngine;