Running Simulations on the Cloud for Reinforcement Learning
For patients visiting a large hospital system for the first time it can be overwhelming to figure out where you need to go, or to even find someone who can point you in the right direction. Employees in the hospital have similar struggles when moving samples from one building to another. We’re exploring solutions to these problems using robotics and artificial intelligence.
Microsoft’s AirSim gives a convenient framework for modeling drones and vehicles in a digital scene that can be controlled programmatically. We’ve worked out a proof-of-concept for running a simulation on a remote server and controlling multiple drones in the simulation using an OpenAI Gym environment wrapper. This gives us an easy way to extract observations to train an AI agent using a reinforcement learning model. For the drones there is a package called PX4 which can be used to chart routes between locations in the simulator.
We’re currently working on creating a 3D model of UK’s campus from LiDAR data, and a model of the hospital system from floorplans using Blender and Unreal Engine.