GelSphere：一种基于全方位滚动视觉的触觉传感器，用于在线3D重建和法向力估计
GelSphere: An Omnidirectional Rolling Vision-Based Tactile Sensor for Online 3D Reconstruction and Normal Force Estimation
AI总结：
本文提出GelSphere，一种基于视觉的触觉传感器，用于实时连续表面扫描。通过内部钢球形成轴承层，实现全方位滚动，提升3D重建和法向力估计的精度。
摘要：
我们介绍了GelSphere，一种基于视觉的触觉传感器，用于实时连续表面扫描。不同于传统视觉触觉传感器只能局部感知且滑动时易受损，以及只能沿固定方向滚动的圆柱形触觉传感器，我们的设计实现了表面的全方位滚动。我们通过新颖的传感系统设计实现这一点，该设计在传感器内部有钢球，形成胶体和刚性外壳之间的轴承层，允许在所有轴上滚动。传感器通过Wi-Fi流式传输触觉图像，具有在线大表面重建能力。我们展示了重建精度和图像融合性能的定量结果。结果表明，即使在多方向滚动下，该传感器也能保持几何保真度和高重建精度，实现不间断的表面扫描。
英文摘要：
We present GelSphere, a spherical vision-based tactile sensor designed for real-time continuous surface scanning. Unlike traditional vision-based tactile sensors that can only sense locally and are damaged when slid across surfaces, and cylindrical tactile sensors that can only roll along a fixed direction, our design enables omnidirectional rolling on surfaces. We accomplish this through our novel sensing system design, which has steel balls inside the sensor, forming a bearing layer between the gel and the rigid housing that allows rolling motion in all axes. The sensor streams tactile images through Wi-Fi, with online large-surface reconstruction capabilities. We present quantitative results for both reconstruction accuracy and image fusion performance. The results show that our sensor maintains geometric fidelity and high reconstruction accuracy even under multi-directional rolling, enabling uninterrupted surface scanning.
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