Leveraging symmetry detection to speed up haptic object exploration in robots
Leveraging symmetry detection to speed up haptic object exploration in robots
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DOI：
10.1109/icdl53763.2022.9962206
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发表时间：
2022-09
期刊：
影响因子：
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通讯作者：
Aramis Augusto Bonzini;L. Seminara;Simone Macciò;A. Carfí;L. Jamone
中科院分区：
文献类型：
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作者：
Aramis Augusto Bonzini;L. Seminara;Simone Macciò;A. Carfí;L. Jamone
大多数物体都是对称的。事实上，人类非常擅长通过视觉和触觉来检测对称性，并且他们使用这些信息来促进对其他对象属性的感知，例如形状和大小;总体而言，这有助于人类在非结构化环境中成功操纵对象的能力。受这种人类技能的启发，在本文中，我们提出了一种触觉探索过程，使机器人能够检测对象的对称性，并使用这些信息来估计对象的形状具有更高的精度和更短的时间。我们实现这一目标，通过将对称性的高斯过程模型，并通过引入一种新的策略来检测这种对称性的存在。我们报告的结果与巴克斯特机器人配备了自定义触觉传感器上的抓手：我们表明，当机器人探索未知对称的物体所需的时间来估计对象的形状减少了50%，由于我们的方法。
Most objects are symmetric. In fact, humans are very good at detecting symmetry, both by vision and by touch, and they use such information to facilitate the perception of other object properties, such as shape and size; overall, this contributes to human’s ability to successfully manipulate objects in unstructured environments. Inspired by this human skill, in this paper we propose a haptic exploration procedure that enables a robot to detect object symmetry, and uses such information to estimate the shape of an object with higher accuracy and in less time. We achieve this by incorporating symmetries in a Gaussian Process model, and by introducing a novel strategy to detect the presence of such symmetry. We report results obtained with a Baxter robot equipped with a custom tactile sensor on the gripper: we show that when the robot explores objects with unknown symmetries the time required to estimate the object shape is reduced by up to 50% thanks to our method.