データ駆動と物理ベース手法を組み合わせた自律ゴルフパッティングロボット
Autonomous Golf Putting with Data-Driven and Physics-Based Methods
カメラとニューラルネットワークを使い、物理モデルで事前学習することで、任意の位置からホールインワンするパットを自律的に学習するゴルフロボットを開発した。
著者: Annika Junker, Niklas Fittkau, Julia Timmermann, Ansgar Trächtler
分類: cs.RO, cs.LG, cs.SY, eess.SY, math.OC
原文アブストラクト
We are developing a self-learning mechatronic golf robot using combined data-driven and physics-based methods, to have the robot autonomously learn to putt the ball from an arbitrary point on the green. Apart from the mechatronic control design of the robot, this task is accomplished by a camera system with image recognition and a neural network for predicting the stroke velocity vector required for a successful hole-in-one. To minimize the number of time-consuming interactions with the real system, the neural network is pretrained by evaluating basic physical laws on a model, which approximates the golf ball dynamics on the green surface in a data-driven manner. Thus, we demonstrate the synergetic combination of data-driven and physics-based methods on the golf robot as a mechatronic example system.