开源触觉传感器提升机器人抓取可复现性与易用性
GelSlim 4.0: Focusing on Touch and Reproducibility
- 基于视觉的触觉传感器，结构简化且可自由改装
- 支持抓握姿态估计与滑动检测，精度满足实际操作需求
- 配套完整制造文档与开源代码，适合研究与爱好者使用
触觉感知为机器人在操作过程中提供丰富反馈，支持多种感知与控制能力。本文介绍一款新的开源、基于视觉的触觉传感器，旨在提升科研与爱好者社区中的可复现性与可及性。在GelSlim 3.0基础上，设计实现了两项关键改进：更简易、可修改的指部结构和易于制造的透镜组件。为配合硬件，我们提供了开源感知库，包含深度与剪切场估计算法，支持手内姿态估计、滑动检测等操作任务。传感器配备完整的制造说明文档，确保不同技术水平用户均可顺利制作。通过广泛的用户体验测试验证了其可复现性。项目资料、代码与数据详见官网：https://www.mmintlab.com/research/gelslim-4-0/
原文摘要 · Abstract (English)
Tactile sensing provides robots with rich feedback during manipulation, enabling a host of perception and controls capabilities. Here, we present a new open-source, vision-based tactile sensor designed to promote reproducibility and accessibility across research and hobbyist communities. Building upon the GelSlim 3.0 sensor, our design features two key improvements: a simplified, modifiable finger structure and easily manufacturable lenses. To complement the hardware, we provide an open-source perception library that includes depth and shear field estimation algorithms to enable in-hand pose estimation, slip detection, and other manipulation tasks. Our sensor is accompanied by comprehensive manufacturing documentation, ensuring the design can be readily produced by users with varying levels of expertise. We validate the sensor's reproducibility through extensive human usability testing. For documentation, code, and data, please visit the project website: https://www.mmintlab.com/research/gelslim-4-0/
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