Changelog

v0.8.0 — Bittle-only Public Release (2026-06-18)

Platform freeze (preserve ≠ delete): the public main branch is scoped to the Petoi Bittle X. Go2 (ablation) and Freenove (sim-to-real) are kept as paper checkpoints — tags v0.4.1-paper1, v0.4.3-paper2, plus v0.7-go2-freenove-final for the last dual-platform main.
Manifest-driven public sync: the public file set is resolved from a generated manifest (the import closure of the Bittle entry points plus static assets) — no wildcard copy, with a private-pattern leak scan. Run outputs, checkpoints, raw meshes, telemetry and internal docs stay private.
README rewritten Bittle-first + honest-claims sweep: overclaim language removed. The published Go2 benchmark (45.15 m) is framed honestly — it trains on an external shaped reward via R-STDP on top of an innate CPG gait; the SNN + cerebellum’s own contribution over CPG-only is ≈+11% distance plus a variance collapse and zero falls. “From scratch / no external reward” describes only the separate intrinsic-reward line, never the benchmark numbers.
Docs site brought to v0.8.0: Architecture, Documentation, Hardware and Getting Started updated Bittle-first with the WiFi-bridge workflow; Go2/Freenove preserved by reference to Papers 1 and 2.
Package version src/__init__.py → 0.8.0 (closes the prior tag/CHANGELOG drift).

Asymmetric stride steering replaces Z-offset (proven useless via hardware test)
PID closed-loop with IMU feedback — automatic drift compensation, no calibration needed
I-term eliminates steady-state drift offset
CompetenceGate v0.5.0 — stability-primary (no longer requires speed for actor handoff)
Meta-Learning Loop Phase A-D: EpisodeAnalyzer, StrategyAdapter, CuriosityExplorer, HypothesisGenerator
Drift profile v3 — yaw rate updated from -0.4 to -1.5 deg/s based on walking-load measurements
World-centered minimaps in renderer with reach radius circle
Hardware validated: dog approaches light (0.52m → 0.17m in 60s)
9 bugs found and fixed in one session

LightMemory — remembers last known light direction when target disappears
Hardware drift simulation — measured drift injected into MuJoCo via xfrc_applied
SNN alignment — 232 → 560 neurons (Freenove), continuous topology scaling
SpatialMap persistence — grid, landmarks, trail saved/restored across sessions
FLOG v1.2 — phototaxis navigation fields, brain map snapshots

Phototaxis — VOR steering toward light, waypoint system, run-and-tumble
6× speedup — Synaptogenesis O(N²) buffer fix, dense SNN threshold, R-STDP lazy rebuild
100k steps in 30 min instead of 5+ hours

train_baby.py — autonomous learning without external reward
Drift root cause — bilateral MH→Output weight asymmetry identified and fixed

10-seed ablation: SNN+Cerebellum 45.15±0.67m vs from-scratch PPO 12.83±7.78m (3.5×)
Recovery Learning (4-phase RightingReflex)
Paper 1 published: aiXiv 260301.000002