01205nas a2200181 4500008004100000245007600041210006900117260004700186520056100233653002300794653002100817100001700838700001700855700001300872700001900885700001600904856010300920 2019 eng d00aReinforcement Learning for Autonomous Driving using CAT Vehicle Testbed0 aReinforcement Learning for Autonomous Driving using CAT Vehicle aTucsonbThe University of Arizonac08/20193 a
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.
10aAutonomous Systems10aMachine Learning1 aNguyen, John1 aHuynh, Hoang1 aAv, Eric1 aBhadani, Rahul1 aBose, Tamal uhttp://csl.arizona.edu/content/reinforcement-learning-autonomous-driving-using-cat-vehicle-testbed