センサベース制御のためのリヤプノフ安定な適応型感覚運動モデル近似法
A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control
フィードバック信号のみから未知の感覚運動モデルを複数の適応ユニットで局所的に推定し、リヤプノフ安定性を保証する手法を提案した論文。
著者: David Navarro-Alarcon, Jiaming Qi, Jihong Zhu, Andrea Cherubini
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
In this article, we present a new scheme that approximates unknown sensorimotor models of robots by using feedback signals only. The formulation of the uncalibrated sensor-based regulation problem is first formulated, then, we develop a computational method that distributes the model estimation problem amongst multiple adaptive units that specialise in a local sensorimotor map. Different from traditional estimation algorithms, the proposed method requires little data to train and constrain it (the number of required data points can be analytically determined) and has rigorous stability properties (the conditions to satisfy Lyapunov stability are derived). Numerical simulations and experimental results are presented to validate the proposed method.
