ステレオ画像ベース視覚サーボにおける局所解回避のためのフィードフォワードYoulaパラメータ化法
A Novel Feedforward Youla Parameterization Method for Avoiding Local Minima in Stereo Image Based Visual Servoing Control
ステレオカメラの視覚サーボ制御において、フィードフォワード制御とYoulaパラメータ化フィードバックを組み合わせることで、局所解に陥らずに目標姿勢へ正確に到達する手法を提案した。
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著者: Rongfei Li, Francis Assadian
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
In robot navigation and manipulation, accurately determining the camera's pose relative to the environment is crucial for effective task execution. In this paper, we systematically prove that this problem corresponds to the Perspective-3-Point (P3P) formulation, where exactly three known 3D points and their corresponding 2D image projections are used to estimate the pose of a stereo camera. In image-based visual servoing (IBVS) control, the system becomes overdetermined, as the 6 degrees of freedom (DoF) of the stereo camera must align with 9 observed 2D features in the scene. When more constraints are imposed than available DoFs, global stability cannot be guaranteed, as the camera may become trapped in a local minimum far from the desired configuration during servoing. To address this issue, we propose a novel control strategy for accurately positioning a calibrated stereo camera. Our approach integrates a feedforward controller with a Youla parameterization-based feedback controller, ensuring robust servoing performance. Through simulations, we demonstrate that our method effectively avoids local minima and enables the camera to reach the desired pose accurately and efficiently.
