用物理仿真生成抓取模板，辅助机器人在遮挡下完成复杂零件非捏取拆解。
Affordance-Guided Enveloping Grasp Demonstration Toward Non-destructive Disassembly of Pinch-Infeasible Mating Parts
- 通过物理仿真预生成多种包裹式抓取方案
- 可视化颜色梯度显示抓取质量，提升操作员判断力
- 适用于视觉遮挡严重、几何约束复杂的实际拆解场景
机器人拆解复杂配合部件时常无法实现捏取抓握，需采用多指包裹式抓取。然而仅依赖2D摄像头易受视觉遮挡和几何限制影响，难以有效教学抓取动作。为此，我们提出一种基于可及性引导的遥操作方法，通过物理仿真预先生成包裹式抓取候选方案，构建可及性模板（Affordance Templates, ATs），并以颜色梯度可视化其抓取质量，增强操作者感知。仿真结果表明该方法具有跨多种组件的通用性。真实机器人实验验证，基于AT的视觉增强可使操作员在严重视觉与几何约束下，有效选择并教学包裹式抓取策略，成功实现非破坏性拆解。
原文摘要 · Abstract (English)
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.
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