Engineering Commons^™

Dqn: Deep Q-Learning For Autonomous Navigation, Leonardo Garrido Alvarez

Kansas State University Undergraduate Research Conference

This project deals with autonomous mobile robots trained using reinforcement learning, a branch of machine learning (the science of improving problem-solving performance based on experience) based on choosing actions to maximize rewards from various environments. This is a form of behavioral learning that is observed in nature and thus more biologically plausible than cognitive models based on labeled data provided by a teacher (supervised learning). We developed an experimental test bed by implementing Deep Q-Networks (DQN), a form of reinforcement learning, for goal-oriented navigation and obstacle avoidance tasks using a TurtleBot3 Burger robot and in the gazebo simulation environment for …