提出新方法避免立体视觉伺服中的局部最优问题
A Novel Feedforward Youla Parameterization Method for Avoiding Local Minima in Stereo Image Based Visual Servoing Control
- 用前馈+Youla参数化反馈控制，解决立体视觉伺服的过约束问题
- 仿真显示可准确高效到达目标位姿，避免陷入局部最优
- 适合需要高精度视觉定位的机器人导航与操作场景
在机器人导航与操作中，精确确定相机相对于环境的姿态对任务执行至关重要。本文系统证明该问题对应于透视三点（P3P）模型，即利用三个已知三维点及其对应的二维图像投影来估计立体相机姿态。在基于图像的视觉伺服（IBVS）控制中，系统处于过约束状态：立体相机的6个自由度需与场景中9个观测到的二维特征对齐。当约束数量超过自由度时，全局稳定性无法保证，相机在伺服过程中可能陷入远离期望配置的局部最小值。为解决此问题，我们提出一种新颖的控制策略，用于精确定位标定后的立体相机。该方法将前馈控制器与基于Youla参数化的反馈控制器相结合，确保了鲁棒的伺服性能。通过仿真验证，所提方法能有效避免局部最小值，使相机准确高效地到达目标位姿。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。