# Zhefan-Xu/NavRL

[IEEE RA-L'25] NavRL: Learning Safe Flight in Dynamic Environments (NVIDIA Isaac/Python/ROS1/ROS2)

Repository: https://github.com/Zhefan-Xu/NavRL
Canonical: https://ross.abutalabs.com/products/navrl
Language: C++
License: MIT
License Family: permissive
Topics: collision-avoidance, isaac-sim, nvidia-isaac, reinforcement-learning, robot-navigation, robotics, ros1-noetic, ros2-humble, embodied-ai
Last push: 2025-07-03T23:47:19+00:00

## Health v2 (maintenance only)
Score: 33/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 29, release rhythm 35, longevity 40
- inputs: {"age_days": 567, "days_push": 426, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1587, forks 168 (observed 2026-08-28T04:05:07.913241+00:00)

## What it is
NavRL is a reinforcement learning framework for safe robot and UAV navigation in dynamic environments, published at IEEE RA-L 2025. It includes training in NVIDIA Isaac Sim, pretrained models, and ROS1/ROS2 deployment packages for velocity-controlled robots.

## Use cases
- train a UAV navigation policy in Isaac Sim with reinforcement learning
- deploy a learned collision-avoidance controller on a ROS1 or ROS2 robot
- run quick demos of navigation among dynamic obstacles and multi-robot scenarios
- extend safe navigation to any velocity-controlled robot platform
- reproduce results from the NavRL RA-L 2025 paper

## When to choose
- you need learned, reactive collision avoidance in dynamic environments
- your robot uses velocity-based control and runs ROS1 Noetic or ROS2 Humble
- you want GPU-accelerated training in NVIDIA Isaac Sim with a pretrained model to start from

## When to avoid
- you need static-map global path planning rather than local reactive navigation
- your platform is not Linux/ROS-based or does not accept velocity commands
- you need a production-grade, commercially supported navigation stack

## Facets
- artifact type: library
- maturity: active
- function: reinforcement-learning, simulation, robotics
- domain: robotics, reinforcement-learning, autonomous-vehicles, simulation
- platform: python, cpp
- tags: uav-navigation, collision-avoidance, isaac-sim, ros1-noetic, ros2-humble, dynamic-environments, velocity-control, embodied-ai, linux, ros

## Member repositories
- Zhefan-Xu/NavRL (main) score 33

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:07.913241+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:55:21.947730+00:00, confidence not recorded.
  - readme: https://github.com/Zhefan-Xu/NavRL (fetched 2026-08-28T04:05:07.913241+00:00, sha bfebc0c308ab)
- Data as of 2026-08-30T08:39:29.467469+00:00.