Precisely grasping an object is a challenging task due to pose uncertainties. Conventional methods have used cameras and fixtures to reduce object uncertainty. They are effective but require intensive preparation, such as designing jigs based on the object geometry and calibrating cameras with high-precision tools fabricated using lasers. In this study, we propose a method to reduce the uncertainty of the position and orientation of a grasped object without using a fixture or a camera. Our method is based on the concept that the flat finger pads of a parallel gripper can reduce uncertainty along its opening/closing direction through flat surface contact. Three orthogonal grasps by parallel grippers with flat finger pads collectively constrain an object's position and orientation to a unique state. Guided by the concepts, we develop a regrasp planning and admittance control approach that sequentially finds and leverages three orthogonal grasps of two robotic arms to eliminate uncertainties in the object pose. We evaluated the proposed method on different initial object uncertainties and verified that the method has satisfactory repeatability accuracy. It outperforms an AR marker detection method implemented using cameras and laser jet printers under standard laboratory conditions.

翻译：精确抓取物体因位姿不确定性而成为一项具有挑战性的任务。传统方法采用相机与夹具来降低物体位姿的不确定性。这些方法虽然有效，但需要大量准备工作，例如根据物体几何形状设计夹具，以及使用激光制造的高精度工具校准相机。本研究提出一种无需使用夹具或相机即可降低被抓取物体位置与方向不确定性的方法。该方法基于以下原理：平行夹爪的平坦指垫可通过平面接触降低沿其开合方向的不确定性。具有平坦指垫的平行夹爪执行三次正交抓取，可共同将物体的位置与方向约束至唯一确定状态。基于此原理，我们开发了一种重抓规划与导纳控制方法，通过顺序寻找并利用两个机械臂的三次正交抓取来消除物体位姿的不确定性。我们在不同初始物体位姿不确定性条件下评估了所提方法，验证了该方法具有令人满意的重复定位精度。在标准实验室条件下，其性能优于使用相机与激光喷墨打印机实现的AR标记检测方法。