視覚予測制御のための運動メモリ
A memory of motion for visual predictive control tasks
オフラインで構築した軌道群をメモリとして保持し、k近傍法やガウス過程回帰で参照することで、視覚予測制御をウォームスタート付きで高速かつ高精度に実行する手法を提案した。7軸マニピュレータの実験で有効性を示した。
著者: Antonio Paolillo, Teguh Santoso Lembono, Sylvain Calinon
分類: cs.RO, cs.CV
原文アブストラクト
This paper addresses the problem of efficiently achieving visual predictive control tasks. To this end, a memory of motion, containing a set of trajectories built off-line, is used for leveraging precomputation and dealing with difficult visual tasks. Standard regression techniques, such as k-nearest neighbors and Gaussian process regression, are used to query the memory and provide on-line a warm-start and a way point to the control optimization process. The proposed technique allows the control scheme to achieve high performance and, at the same time, keep the computational time limited. Simulation and experimental results, carried out with a 7-axis manipulator, show the effectiveness of the approach.
