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The objective of the project is to explore synergies between classicalcontrol algorithms such as PID and contemporary reinforcement learningalgorithms to come up with a pragmatic control mechanism to control theCrazyFlie 2.X quadrotor. The primary objective would be performing PID tuningusing reinforcement learning strategies. The secondary objective is to leveragethe learnings from the first task to implement control for navigation byintegrating with the lighthouse positioning system. Two approaches areconsidered for navigation, a discrete navigation problem using Deep Q-Learningwith finite predefined motion primitives, and deep reinforcement learning for acontinuous navigation approach. Simulations for RL training will be performedon gym-pybullet-drones, an open-source gym-based environment for reinforcementlearning, and the RL implementations are provided by stable-baselines3

Reinforcement Learning-Based Control of CrazyFlie 2.X Quadrotor