Visualization of Deep Reinforcement Autonomous Aerial Mobility Learning Simulations

Gusang Lee, Won Joon Yun, Soyi Jung, Joongheon Kim, Jae-Hyun Kim

Abstract: This demo abstract presents the visualization of deep reinforcement learning (DRL)-based autonomous aerial mobility simulations. In order to implement the software, Unity-RL is used and additional buildings are introduced for urban environment. On top of the implementation, DRL algorithms are used and we confirm it works well in terms of trajectory and 3D visualization.