发表机构
Institut de Robòtica i Informàtica Industrial, CSIC-UPC; Universitat Politècnica de Catalunya（工业机器人研究所，CSIC-UPC; 加泰罗尼亚理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种简易夹爪接口模型，通过位置约束和抓取体积实现模拟器无关的布料抓取，并在真实机器人上验证其有效性。
AI 中文摘要
本文提出了一种专门为简化机器人控制方法部署而设计的布料操作抓取模型。该模型鲁棒、快速且易于实现，同时避免了夹爪与布料之间的接触和摩擦考虑，转而采用简单的位置约束。夹爪由其位姿、钳口状态和附着的抓取体积来描述。考虑了两种抓取体积：一种用于模拟捏取抓取的轴对齐盒体，以及一种用于模拟点抓取的方形锥体体积。当夹爪闭合时，位于该体积内的离散布料位置被选中，存储在夹爪局部坐标系中，并随夹爪运动而移动。还包含一个简单的挤压步骤，以逐步将选中的布料位置移向抓取区域中心，避免在闭合时产生瞬时位移。该模型可用于任何模拟器，因为它仅需访问离散布料位置以及一种将目标位置作为约束施加的机制。我们将抓取模型与基于约束的不可伸长布料模拟器结合实现，其中抓取通过移动位置等式约束与拉伸、剪切、碰撞和桌面接触投影步骤耦合实现。相同的夹爪轨迹被应用于机器人手臂以折叠一块真实布料，作为模拟与物理布料操作之间的简单桥梁，展示了我们理想化抓取模型的真实性和实用性。
英文摘要
This paper presents a grasping model for cloth manipulation specifically tailored to ease the deployment of robotic control methods. The model is robust, fast and easy to implement avoiding at the same time contact and friction considerations between the gripper and the cloth in favor of simple positional constraints. The gripper is described by its pose, jaw state, and an attached grasping volume. Two kinds of grasping volumes are considered: an axis-aligned box to simulate a pinch grasping and a square pyramidal volume to simulate point grasping. When the gripper closes, the discrete cloth positions lying inside this volume are selected, stored in the local gripper frame, and then transported with the gripper motion. A simple squeezing step is also included to progressively move the selected cloth positions toward the center of the grasping region, avoiding an instantaneous displacement at closure. The model can be used in any simulator as it only requires access to discrete cloth positions and a mechanism for imposing target positions as constraints. We implement our grasping model in conjunction with a constraint-based inextensible cloth simulator, where grasping is implemented as moving positional equality constraints coupled with stretch, shear, collision, and table contact projection steps. The same gripper trajectory is applied on a robot arm to fold a real piece of cloth, serving as a simple bridge between simulation and physical cloth manipulation and showcasing the realism and practicality of our idealized grasping model.
CommentsAccepted for a special session on Hybrid Intelligence at the 23rd International Conference on Informatics in Control, Automation and Robotics, 26-28 October, 2026
