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

翻译：本项目旨在探索经典控制算法（如PID）与现代强化学习算法之间的协同效应，以提出一种用于控制CrazyFlie 2.X四旋翼飞行器的实用控制机制。首要目标为利用强化学习策略实现PID调参。次要目标则是借助第一项任务的学习成果，通过与灯塔定位系统的集成，实现导航控制。针对导航问题，我们考虑两种方法：基于有限预定义运动基元的深度Q学习的离散导航方法，以及面向连续导航的深度强化学习方法。强化学习训练的仿真将在gym-pybullet-drones（一个基于gym的开源强化学习环境）中进行，而强化学习实现由stable-baselines3提供。