基于 affordance 的包裹抓取演示：非破坏性拆卸难以抓取的啮合部件
Affordance-Guided Enveloping Grasp Demonstration Toward Non-destructive Disassembly of Pinch-Infeasible Mating Parts
AI总结：
本文提出一种基于 affordance 的遥控方法，通过物理模拟预生成包裹抓取候选方案，利用颜色梯度增强操作员感知，实验证明该方法能有效指导实际拆卸任务。
摘要：
复杂的啮合组件的机器人拆卸往往使夹持抓取不可行，需要多指包裹抓取。然而，仅依赖2D摄像头会受到视觉遮挡和几何约束的限制。为此，我们提出一种基于 affordance 的遥控方法，通过物理模拟预生成包裹抓取候选方案。这些 Affordance 模板 (ATs) 通过颜色梯度反映抓取质量以增强操作员感知。模拟显示该方法在各种组件上具有通用性。实际机器人实验验证了 AT 基础的视觉增强能够使操作员有效选择和教学包裹抓取策略，即使在严重的视觉和几何约束下也能实现。
英文摘要：
Robotic disassembly of complex mating components often renders pinch grasping infeasible, necessitating multi-fingered enveloping grasps. However, visual occlusions and geometric constraints complicate teaching appropriate grasp motions when relying solely on 2D camera feeds. To address this, we propose an affordance-guided teleoperation method that pre-generates enveloping grasp candidates via physics simulation. These Affordance Templates (ATs) are visualized with a color gradient reflecting grasp quality to augment operator perception. Simulations demonstrate the method's generality across various components. Real-robot experiments validate that AT-based visual augmentation enables operators to effectively select and teach enveloping grasp strategies for real-world disassembly, even under severe visual and geometric constraints.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
