外观
论文arXiv 2609.181651 个月前
LUMO：面向可重复全指接触观测的发光接触形态设计
原文链接：LUMO: Designing Luminous Contact Morphology for Repeatable Whole-Finger Contact Observation（arXiv 2609.18165 · 发布日期：2026-09-16）
LUMO: Designing Luminous Contact Morphology for Repeatable Whole-Finger Contact Observation
LUMO用LED照明可变形硅胶垫观测手指接触位置，结合仿真优化，并在压入与双指抓取中验证。
核心要点
- 低阻抗手指同一关节力矩可能对应不同接触位置与力，需知道沿指接触点。
- 嵌入LED照亮顺应硅胶垫，接触变形改变侧面出光图案，使位置外部可观测。
- 联合优化垫轮廓、刚性载体和侧向空腔，兼顾低预载顺应与光学响应分离。
- 两种硅胶、六位置和两种球形压头下，邻位分离提升15%--59%，力估计MAE为1.44 N。
验证范围与局限：验证范围包括两种硅胶、六个接触位置、10/30 mm球形压头，以及双指手抓取中的多连杆侧面响应。
英文摘要 (Abstract)
A low-impedance robot finger reports through joint torque how strongly it is loaded, but the same torque can arise from a small force near the fingertip or a large force near the joint. Resolving the force therefore requires knowing where along the finger contact occurred. LUMO makes that location externally observable. Embedded LEDs illuminate a compliant silicone pad, and contact deforms the pad so that light emerging from the finger's side changes in a pattern set by where the load acts. Because the same structure also carries the contact load, we optimize its cross-section, including the pad profile, rigid carrier, and lateral void, for two behaviors at once. Mechanically, the pad conforms under low preload while the carrier increasingly restricts further deformation as load rises. Optically, different contact locations produce separated responses on the finger's side. The search uses rigid--soft contact simulation, ray tracing, and multi-objective Bayesian optimization. Across two silicones, six contact locations, and 10- and 30-mm spherical indenters, the optimized morphologies improve neighboring-location separation relative to variation from re-establishing contact by (15)--(59%). Estimating contact location from the optical response using the known LED spacing and combining it with joint torque gives (1.44~\mathrm{N}) normal-force MAE over 931 samples. In a two-finger hand, localized side responses appear on several links simultaneously during grasps.
作者：Dong Ho Kang, Youngsu Ko, Luis Sentis
来源
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