基于视觉的机器人布料展开6自由度抓取姿态估计
Vision-Based 6-DoF Grasp Pose Estimation for Robot Cloth Unfolding
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中文总结 AI 辅助
针对布料展开中感知模糊与抓取点选择难题，提出CeDiRNet-6DoF框架，联合预测抓取点与6自由度姿态，在ICRA 2024竞赛中达最优性能，为机器人布料操作奠定基础。
中文摘要 AI 辅助
布料操作是一项具有挑战性的任务，因为布料具有可变形和高维的特性，这导致复杂的交互动力学以及由于褶皱、边缘和抓取点等关键视觉线索频繁遮挡而产生的感知模糊性。在这项工作中，我们采用空中重新抓取策略来解决布料展开问题，其中一个机械臂握住布料，而另一个机械臂在最优选定的点抓取布料以将其展开。为此，我们提出了CeDiRNet-6DoF，这是一个深度学习框架，能够从观察到的布料配置中联合预测有效的抓取点和完整的6自由度抓取姿态。通过将密集的3D抓取回归与分割以及正弦-余弦编码的欧拉角相结合，所提出的方法能够可靠地估计最大化展开布料面积的抓取配置。我们在ICRA 2024布料竞赛框架内的双臂机器人设置上广泛评估了CeDiRNet-6DoF，取得了最先进的性能。一项消融研究进一步验证了关键设计组件的优势，包括联合分割、背景随机化和图像裁剪。这些结果确立了CeDiRNet-6DoF作为在非结构化环境中可靠机器人布料操作的稳健且多功能的基石。
英文摘要
Cloth manipulation is a challenging task due to the deformable and high-dimensional nature of cloth, which leads to complex interaction dynamics and perceptual ambiguity arising from frequent occlusions of critical visual cues such as folds, edges, and grasp points. In this work, we tackle cloth unfolding using a regrasping-in-the-air strategy, where one manipulator holds the cloth while the other grasps it at an optimally selected point to unfold it. To this end, we propose CeDiRNet-6DoF, a deep learning framework that jointly predicts effective grasp points and the complete 6-DoF grasp pose from the observed cloth configuration. By integrating dense 3D grasp regression with segmentation and sine-cosine-encoded Euler angles, the proposed method reliably estimates the grasp configuration that maximizes the unfolded cloth area. We extensively evaluated CeDiRNet-6DoF on a bimanual robotic setup within the ICRA 2024 Cloth Competition framework, achieving state-of-the-art performance. An ablation study further validates the benefits of key design components, including joint segmentation, background randomization, and image cropping. These results establish CeDiRNet-6DoF as a robust and versatile foundation for reliable robotic cloth manipulation in unstructured environments.
发表机构
- Faculty of Computer and Information Science, University of Ljubljana（卢布尔雅那大学计算机与信息科学学院）
- Jožef Stefan International Postgraduate School（约热夫·斯特凡国际研究生院）
- Jožef Stefan Institute（约热夫·斯特凡研究所）
机构由 AI 辅助整理，请以论文原文为准。
