title_body: Can Reinforcement Learning be used for UAV waypoint control? I want to make a drone which can follow static and dynamic waypoints. I am a total beginner in the drone field so I can't figure out whether I should use Reinforcement Learning or other learning methods for the drone to make it follow both static and dynamic waypoints. If RL is the best choice for the task, then how would I go about training the model before uploading it to the flight controller. And if RL is not required, then what should I use in order to achieve this task?
  
  Currently, I have no clue about which software to use for the task. I am very interested in this field and I would love to learn more. Please let me know how I should begin with this task.
upvoted_answer: Reinforcement Learning can be used for UAV control. This video details a method to use RL for quadcopters.
  
  In summary, you program a model of your UAV that effectively simulates your drone.
  You then create a policy and value neural network to control your drone and train it using your simulation.
  
  I'm pretty sure similar methods are used in zipline's autonomous drone delivery network that manages 65% of the entire country of Rwanda's blood deliveries.