滑空弾の誘導制御のための強化学習
Reinforcement Learning for Gliding Projectile Guidance and Control
光学誘導滑空機の制御則を強化学習で構築し、カメラで検出した目標を高精度に追跡・誘導できることを示した研究。
著者: Joel Cahn, Antonin Thomas, Philippe Pastor
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
This paper presents the development of a control law, which is intended to be implemented on an optical guided glider. This guiding law follows an innovative approach, the reinforcement learning. This control law is used to make navigation more flexible and autonomous in a dynamic environment. The final objective is to track a target detected with the camera and then guide the glider to this point with high precision. Already applied on quad-copter drones, we wish by this study to demonstrate the applicability of reinforcement learning for fixed-wing aircraft on all of its axis.