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.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
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.
What is 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.
Is DRL-robot-navigation open source?
DRL-robot-navigation is an open-source project. It is released under the MIT license.
Is DRL-robot-navigation free?
Yes. DRL-robot-navigation is free and open source — you can use, modify and self-host it.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://opensourceai.tech/project/reiniscimurs-drl-robot-navigation.html)
