Reinforcement Learning for Autonomous Driving using CAT Vehicle Testbed
|Reinforcement Learning for Autonomous Driving using CAT Vehicle Testbed
|Year of Publication
|Nguyen, J, Huynh, H, Av, E, Bhadani, R, Bose, T
|CAT Vehicle Research Experience for Undergraduates
|The University of Arizona
|Autonomous Systems, Machine Learning
We discuss a deep reinforcement learning implementation using the CAT Vehicle Testbed and discuss the merits of simulation-based deep reinforcement learning. After implementing a simple 3 layered neural network which learned using deep Q-learning, we found some challenges associated with ROS and Gazebo. In spite of these challenges, we demonstrate that our reinforcement learning architecture can teach a car to avoid obstacles. With these preliminary results, we discuss what new things we can do and how we can implement more advanced methods.