面向增材制造的物体特定被动夹具的机器人感知计算设计
Robot Aware Computational Design of Object Specific Passive Grippers for Additive Manufacturing
- QSS AI and Robotics Lab（QSS人工智能与机器人实验室）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出端到端计算流程，结合多种技术生成适配物体、机器人的增材制造被动夹具，经多关卡验证，设计保留关键域，处于数字筛选状态。
AI中文摘要：
本文提出了一种端到端计算流程，可将选定的物体网格、测量的物体状态以及选定的六轴机器人转换为特定于物体的、未致动的、可增材制造的夹具。该方法结合了精确网格RGB-D/ICP位姿配准、确定性表面接触采样、不确定性感知力矩筛选、六种被动抓取机构中的选择、物体贴合表面合成、全方向机器人逆运动学、扫掠体积感知制造域、定向熔融沉积有限元筛选以及约束三维SIMP拓扑优化。与将抓取选择、工具几何、运动和结构设计视为独立问题的工作流程不同，每个导出的设计都通过可追溯的设计标识符与源网格、物体位姿、机器人法兰、接触集和插入假设绑定。本文推导了所实现的配准、接触、配合公差、有限元和密度优化方程，并证明了数值构造的三个特性：节点载荷保持、SIMP插值下的单调柔顺性灵敏度以及拓扑后处理后的体素域包含性。四个存档的特定物体尝试——兔子、相机法兰、3DBenchy和多面胸像——均满足名义配合、不确定力矩、运行时扫掠以及基线/后拓扑有限元分析（FEA）关卡。刻意放大的±3毫米、±5度位姿应力检查对这些设计进行了区分，在160次模拟试验中保留了29至134次。它们重构的拓扑保留了92.0%至97.6%的有限元（FE）域，因为功能区域受到保护。存档的机器人照片定性展示了相应的打印组件，而名义材料属性以及缺乏试样校准、仪器化测试使这四个设计均处于数字筛选状态，而非可操作发布状态。
英文摘要：
This paper presents an end-to-end computational pipeline that converts a selected object mesh, a measured object state, and a selected six-axis robot into an object-specific, unactuated, additively manufacturable gripper. The method couples exact-mesh RGB-D/ICP pose registration, deterministic surface-contact sampling, uncertainty-aware wrench screening, selection among six passive capture mechanisms, object-conformal surface synthesis, full-orientation robot inverse kinematics, a swept-volume-aware manufacturing domain, directional fused-deposition finite-element screening, and constrained three-dimensional SIMP topology optimization. Unlike workflows that treat grasp selection, tool geometry, motion, and structural design as separate problems, every exported design is bound to the source mesh, object pose, robot flange, contact set, and insertion hypothesis by a traceable design identifier. We derive the implemented registration, contact, fit-tolerance, finite-element, and density-optimization equations and prove three properties of the numerical construction: nodal load preservation, monotonic compliance sensitivity under SIMP interpolation, and voxel-domain containment after topology post-processing. Four archived object-specific attempts - a rabbit, camera flange, 3DBenchy, and faceted bust - meet the nominal fit, uncertain-wrench, runtime-sweep, and baseline/post-topology FEA gates. A deliberately enlarged +/-3 mm, +/-5 degree pose stress check differentiates the designs, retaining 29-134 of 160 simulated trials. Their reconstructed topologies retain 92.0-97.6% of the FE domain because functional regions are protected. Archived robot photographs show the corresponding printed assemblies qualitatively, while nominal material properties and absent coupon-calibrated, instrumented tests keep all four at digital-screening status rather than operational release.
