  The objective of the project is to explore synergies between classical
control algorithms such as PID and contemporary reinforcement learning
algorithms to come up with a pragmatic control mechanism to control the
CrazyFlie 2.X quadrotor. The primary objective would be performing PID tuning
using reinforcement learning strategies. The secondary objective is to leverage
the learnings from the first task to implement control for navigation by
integrating with the lighthouse positioning system. Two approaches are
considered for navigation, a discrete navigation problem using Deep Q-Learning
with finite predefined motion primitives, and deep reinforcement learning for a
continuous navigation approach. Simulations for RL training will be performed
on gym-pybullet-drones, an open-source gym-based environment for reinforcement
learning, and the RL implementations are provided by stable-baselines3
