強化学習によるCrazyFlie 2.Xクアッドロータの制御
Reinforcement Learning-Based Control of CrazyFlie 2.X Quadrotor
PID制御と強化学習を組み合わせ、CrazyFlie 2.XのPIDゲイン調整とライトハウス測位を用いたナビゲーション制御をシミュレーションで検討した。
著者: Arshad Javeed, Valentín López Jiménez
分類: cs.RO, cs.LG
原文アブストラクト
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
