Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased 

Control debug panel: real-time steering/throttle visualization (PyQt6 renderer)
Observation debug overlay: live observation values overlay on the map (PyQt6 renderer)
ONNX export: convert SB3 models to ONNX for sim-to-real transfer via OnnxPolicyRunner
Norm bounds extraction: save normalization bounds to config for reuse in external packages
Custom neural network architecture: configurable layer sizes via net_arch in RL config
Morris sensitivity analysis: parameter sensitivity analysis script for STD model
Observation sensitivity analysis: script for analyzing observation feature importance
Regression tests: tests for action ordering and other previously encountered bugs
Trajectory comparison script: compare KS, ST, STD model trajectories for sim2real validation

Recovery training: dedicated training mode (training_mode: "recover") with recovery-specific rewards, resets, and evaluation
Curriculum learning: CurriculumLearningCallback that gradually expands recovery state initialization ranges as agent success rate improves
Transfer learning: transfer pretrained model weights to new tasks with optional critic reset and log_std re-initialization
MPC controllers: Kinematic MPC (KMPC) and Single-Track MPC (STMPC) via acados integration
Multi-map training: train across multiple maps in parallel environments
Sparse width observations: sparse_width_obs config to reduce observation dimensionality when track width varies little
P/PD controllers: simple proportional controllers for benchmarking recovery performance
Performance metrics: beta-r phase plane analysis, recovery trajectory plotting, controller comparison metrics
PyPI publishing via publish.yml GitHub Actions workflow (triggered on tag push)
ReadTheDocs documentation site with Sphinx RTD theme
Logos, favicon, and branding assets

Refactored package for PyPI publishing (renamed f1tenth_gym to gymkhana)
Migrated from Black to Ruff for linting, formatting, and import sorting with pre-commit hooks
Refactored controllers with abstract base class
Refactored training scripts with shared train_common.py and train_utils.py
Updated map loading to use maintained source for better compatibility
Reorganized project structure (analysis, figures, plans into dedicated directories)

Drift dynamics: Single Track Drift (STD) model with PAC2002 tire physics
Reverse/random driving direction: track_direction config option (normal, reverse, random) for balanced cornering training
State reset: env.reset(options={"states": ...}) for full 7-d state initialization (STD model)
Arc-length visualization: render arc-length annotations along the centerline for Frenet coordinate debugging
Observation types: FeaturesObservation (drift) with slip angle, lookahead curvatures/widths; observation and action normalization
Predictive collision: TTC-based collision checking as alternative to Frenet-based
Wall deflection mode: configurable track boundary behavior (boundary vs. wall collision)
Progress reward gain: configurable progress_gain multiplier for forward progress reward
Frenet projection debugging: debug_frenet_projection visualization option
Lookahead curvature visualization: render lookahead sampling points ahead of the vehicle
Wandb integration: experiment tracking, model logging, download, and resume from wandb
Performance metrics: beta-r phase plane analysis, recovery trajectory plotting
PPO training infrastructure with SB3 and parallel environments

Wraparound bug in progress tracking (robust fix with unit tests)
Normalization logic when both actions and observations are normalized
Reverse direction reset bug where random reset could point vehicle the wrong way due to cached reference line
Reverse direction normalization fix where min/max curvature bounds need to be symmetric