Endowing robots with tactile capabilities opens up new possibilities for their interaction with the environment, including the ability to handle fragile and/or soft objects. In this work, we equip the robot gripper with low-cost vision-based tactile sensors and propose a manipulation algorithm that adapts to both rigid and soft objects without requiring any knowledge of their properties. The algorithm relies on a touch and slip detection method, which considers the variation in the tactile images with respect to reference ones. We validate the approach on seven different objects, with different properties in terms of rigidity and fragility, to perform unplugging and lifting tasks. Furthermore, to enhance applicability, we combine the manipulation algorithm with a grasp sampler for the task of finding and picking a grape from a bunch without damaging~it.

翻译：赋予机器人触觉能力为其与环境的交互开启了新的可能性，包括处理易碎和/或软质物体的能力。本研究为机器人夹爪配备了低成本基于视觉的触觉传感器，并提出了一种无需先验物体属性知识即可适应刚性和软质物体的操控算法。该算法基于触觉与滑移检测方法，通过分析触觉图像相对于参考图像的变化来实现。我们在七种具有不同刚度和易碎性属性的物体上验证了该方法，用于执行拔取和提举任务。此外，为提升适用性，我们将该操控算法与抓取采样器结合，实现了从葡萄串中无损搜寻并摘取单颗葡萄的任务。