Visualization of Deep Reinforcement Autonomous Aerial Mobility Learning Simulations
This is an incremental demonstration for researchers or developers in autonomous aerial mobility, focusing on visualization rather than algorithmic advancement.
The authors tackled the problem of visualizing deep reinforcement learning simulations for autonomous aerial mobility by implementing a system using Unity-RL and additional urban buildings, and they confirmed it works well in terms of trajectory and 3D visualization without providing concrete numbers.
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.