This work presents a new version of the tactile-sensing finger GelSlim 3.0, which integrates the ability to sense high-resolution shape, force, and slip in a compact form factor for use with small parallel jaw grippers in cluttered bin-picking scenarios. The novel design incorporates the capability to use real-time analytic methods to measure shape, estimate the contact 3D force distribution, and detect incipient slip. To achieve a compact integration, we optimize the optical path from illumination source to camera and other geometric variables in a optical simulation environment. In particular, we optimize the illumination sources and a light shaping lens around the constraints imposed by the photometric stereo algorithm used for depth reconstruction. The optimized optical configuration is integrated into a finger design composed of robust and easily replaceable snap-to-fit fingetip module that allow for ease of manufacture, assembly, use, and repair. To stimulate future research in tactile-sensing and provide the robotics community access to reliable and easily-reproducible tactile finger with a diversity of sensing modalities, we open-source the design and software at https://github.com/mcubelab/gelslim.
翻译:这项工作提出了一种新的触摸感知手指 GelSlim 3.0, 将感知高分辨率形状、 力力和缩缩成一个紧凑成像系数的能力整合在一起, 以便与小型平行的下巴抓手一起在杂乱的垃圾挑选情景中使用。 新的设计包含使用实时分析方法的能力, 以测量形状, 估计接触 3D 力分布, 并检测刚起的滑块。 为了实现压缩整合, 我们优化光学路径, 从照明源到光学模拟环境中的相机和其他几何变量。 特别是, 我们优化照明源和光成像镜头, 围绕用于深度重建的光度测量立体算法所施加的限制。 最优化的光学配置被整合到手指设计中, 由坚固和易于替换的直径可替换的直径翼立模型组成, 以便于制造、 组装、 使用和修补。 为了刺激未来对触摸性测量的研究, 我们为机器人社区提供可靠和容易复制的触控性指, 以及多种感测模式, 我们开源/ ambel. ambel.