无传感器的防损伤抓取

中文摘要 AI 辅助

机器人水果采摘必须牢固握住果实且不造成碰伤，但同一物种内果实的压缩刚度随成熟度变化可达数倍，因此固定抓取力无法覆盖该范围。本文不调整力的大小，而是通过限定变形量实现防损伤：控制器关闭夹持器，直到物体的估计压缩应变达到用户指定的极限ε，仅使用每个伺服夹持器上的编码器位置和电机出力信号，无需触觉或力/扭矩传感器。将基于出力的接触力除以物体刚度的下界，可使停止动作在ε高于接触检测应变底限时被证明是保守的——实际压缩量不超过ε；我们确定并量化了该接触检测应变底限，稳健检测本身会消耗压缩量，且与闭合速度呈线性关系，这使得速度成为明确的吞吐量-柔和度调节旋钮。与手动调整的力阈值不同，ε是经认证、可按尺寸缩放、操作员可解释的损伤极限，也是学习型抓取策略的现成安全动作参数。在MuJoCo仿真中，针对真实水果的刚度范围，采用校准至真实伺服的传感器噪声模型，控制器在整个经认证的ε范围内，对所有中等到高刚度果实实现≥98%的抓取成功率和0%的损伤，这是固定力基线无法达到的；在按刚度分级的3D打印TPU立方体上，其抓取成功率与基线相当，但抓取力约为基线的一半，且软物体损伤从100%降至40%。

英文摘要

Robotic fruit harvesting must hold produce securely without bruising it, yet compression stiffness varies several-fold with ripeness within a single species, so no fixed grip force spans the range. Rather than tune force, we bound deformation: a controller closes the gripper until the object's estimated compression strain reaches a user-specified limit $\varepsilon$, using only the encoder position and motor-effort signal on every servo gripper---no tactile or force-torque sensor. Dividing an effort-based contact force by a lower bound on object stiffness makes the stop provably conservative---true compression stays at or below $\varepsilon$---for any $\varepsilon$ above a contact-detection strain floor we identify and quantify: robust detection itself spends compression, linearly in closing speed, making speed an explicit throughput--gentleness knob. Unlike a hand-tuned force threshold, $\varepsilon$ is a certified, size-scaling, operator-interpretable damage limit, and a ready safe-action parameter for learned grasping policies. In MuJoCo simulation over a realistic fruit-stiffness range, under a sensor-noise model calibrated to the real servo, the controller holds $\ge 98\,\%$ grasp at $0\,\%$ damage across all medium-to-firm stiffnesses for the entire certified $\varepsilon$ range, which neither fixed-force baseline attains; on stiffness-graded 3D-printed TPU cubes it matches baseline grasp success at roughly half the grip force and cuts soft-object damage from $100\,\%$ to $40\,\%$.

发表机构

• Kyushu University（九州大学）

机构由 AI 辅助整理，请以论文原文为准。