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，以开发一种实用的控制机制用于控制CrazyFlie 2.X四旋翼飞行器。首要目标是利用强化学习策略实现PID参数整定。次要目标则是借助第一项任务的研究成果，通过与灯塔定位系统集成，实现导航控制。针对导航任务，本文考虑两种方法：一种基于深度Q学习，采用有限预定义运动基元的离散导航方案；另一种基于深度强化学习的连续导航方法。强化学习训练的仿真在gym-pybullet-drones（一个基于gym开源框架的强化学习环境）中进行，强化学习算法实现由stable-baselines3提供。