Deep Reinforcement Learning approach to Autonomous Navigation

Abstract

In this project we use state-of-the-art RL algorithms to explore the problem of Autonomous Navigation. Specifically, we employ DeepMind's DDPG (Deep Deterministic Policy Gradient) algorithm to learn an agent for navigation in TORCS simulation environment.

Simulation Environment

We use TORCS(gym_torcs) simulation environment for this task.

Demo

Training

Testing

Installation Dependencies:

• Python 2.7
• Keras 1.1.0
• Tensorflow r0.10
• gym_torcs

How to Run?

git clone https://github.com/bhanuvikasr/Deep-RL-TORCS.git
cd DDPG-Keras-Torcs
cp *.* ~/gym_torcs
cd ~/gym_torcs
python ddpg.py 

(Change the flag train_indicator=1 in ddpg.py if you want to train the network)

Credits

Thanks to Yanpanlau