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reiniscimurs/DRL-robot-navigation

Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles. observed · 2026-08-28

github.com/reiniscimurs/DRL-robot-navigation · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

58/100

  • Activity 57
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1773
  • days_rel: n/a
  • days_push: 263
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1356 stars · 193 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A ROS Gazebo simulation project that trains a mobile robot to navigate to random goals while avoiding obstacles using a TD3 deep reinforcement learning network. It includes training and testing scripts, a Gazebo environment with a simulated 3D Velodyne lidar, and TensorBoard logging, based on an ICRA 2022 / IEEE RA-L paper.

Use cases

  • train a robot to navigate to goals with deep reinforcement learning
  • simulate obstacle avoidance for a mobile robot in Gazebo
  • learn TD3 for robot navigation
  • reproduce a DRL robot navigation research paper
  • set up a ROS Gazebo training environment for navigation policies
  • test learned navigation policies with lidar sensor input

When to choose

  • you use ROS Noetic on Ubuntu and want a working DRL navigation setup
  • you want to train or evaluate TD3 policies in a Gazebo simulator
  • you need a reference implementation for lidar-based obstacle avoidance research

When to avoid

  • you need navigation on real hardware out of the box
  • you use ROS 2 or a non-Ubuntu platform
  • you want a general-purpose navigation stack rather than a research/training codebase

Facets

application · maturity active

reinforcement-learning machine-learning deep-learning simulation robotics robotics reinforcement-learning deep-learning simulation python td3 ros gazebo obstacle-avoidance robot-navigation pytorch velodyne linux

1 source

Member repositories

RepositoryRoleHealth v2
reiniscimurs/DRL-robot-navigationmain58

For agents

markdown · JSON · MCP: product_card(name="reiniscimurs/DRL-robot-navigation")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem