Python · MIT
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.
★ 1.4k
Stars
195 forks · 63 open issues
+2.0/wk
Growth · measured
Stars counted between two of our own snapshots roughly a week apart. The repository page gives the exact span.
11.2
Momentum / 100
see the breakdown below
5y ago
Created
last push 10mo ago
Star history
How this score was built
| Component | Weight | Earned | Why |
|---|---|---|---|
| Velocity | 55 | 2.1 | +2.0/wk, log-scaled against a 750/day ceiling |
| Acceleration | 15 | 0.0 | needs 7-day and 30-day rates side by side |
| Freshness | 15 | 0.0 | last push 10mo ago; decays to zero at 180 days |
| Scale | 15 | 9.1 | 1.4k stars, log-scaled against 150k — stops a 3-star repo topping the board |
| Momentum | 100 | 11.2 | sum of the above |
Detail
| Topics | deep-learningdeep-reinforcement-learninggazeboobstacle-avoidanceobstacle-avoidance-robotreinforcement-learningrobot-navigationrostd3 |
| Matched on | ROS2 (ros) |
| Short window | +2 stars over 7 days = 0.3/day |
| Long window | +1 stars over 26 days = 0.0/day |
| Lifetime average | 0.75 stars/day over 1,837 days |
| First seen here | 2026-10-11 |
| Last read | 2d ago |