@conference {470, title = {Reinforcement Learning for Autonomous Driving using CAT Vehicle Testbed}, booktitle = {CAT Vehicle Research Experience for Undergraduates}, year = {2019}, month = {08/2019}, publisher = {The University of Arizona}, organization = {The University of Arizona}, type = {Technical Report}, address = {Tucson}, abstract = {

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.

}, keywords = {Autonomous Systems, Machine Learning}, url = {http://csl.arizona.edu/content/reinforcement-learning-autonomous-driving-using-cat-vehicle-testbed}, author = {John Nguyen and Hoang Huynh and Eric Av and Rahul Bhadani and Tamal Bose} }