HoverPilot

License

Minimal Python 3.10+ client to connect to RealFlight Link (TCP 18083), exchange RC commands, and expose a Gymnasium-compatible hover environment.

Installation

Install the base package from PyPI:

pip install hover-pilot

Install the optional PPO training, evaluation, and reporting dependencies:

pip install "hover-pilot[rl]"

With uv, use uv add hover-pilot or uv add "hover-pilot[rl]".

Quickstart

From a source checkout, install dependencies and run the demo with uv:

uv sync
cp .env.example .env
uv run hoverpilot-demo

Install the optional reinforcement-learning dependencies to train or play a PPO policy:

uv sync --extra rl
uv run hoverpilot-ppo train --timesteps 50000 --save-path ppo_hoverpilot.pt

HoverPilot periodically evaluates the deterministic policy, keeps latest and best checkpoints separately, and stores the complete training state for exact continuation. A repository checkout also includes an example TOML experiment:

uv run hoverpilot-ppo train --config configs/elevator.toml

Evaluate the best checkpoint or generate an HTML summary from a TensorBoard run:

uv run hoverpilot-ppo evaluate --checkpoint ppo_hoverpilot.best.pt
uv run hoverpilot-ppo report runs/hoverpilot-ppo

The user guide describes TOML overrides, checkpoint comparison, full-state resume, evaluation metrics, and HTML reports in detail.

By default HoverPilot connects to RealFlight Link at 127.0.0.1:18083. Set RFLINK_HOST when RealFlight runs on another host or outside the current network namespace.

Gymnasium Environment

import numpy as np

from hoverpilot.config import HOST, PORT
from hoverpilot.envs import HoverPilotHoverEnv

env = HoverPilotHoverEnv(host=HOST, port=PORT, max_episode_steps=250)
observation, info = env.reset()
action = np.asarray([0.0, 0.0, 0.55, 0.0], dtype=np.float32)
observation, reward, terminated, truncated, info = env.step(action)

The action contains aileron, elevator, throttle, and rudder. See the user guide for observation layouts, reward and termination behavior, and trainer modes.

Documentation

License

This project is licensed under the MIT License. See the LICENSE file for details.

Project links

Data verified by PyPI on Aug 15, 2026
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Credits

Author: Kyungwon Chun

GitHub Statistics

Data verified by PyPI on Aug 15, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

MIT
View SPDX License List

Requires

Python >=3.10

Provides Extra

rl

Tags

realflight gymnasium reinforcement-learning ppo

Classifiers

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