Non-Destructive Robotic Assessment of Mango Ripeness via Multi-Point Soft Haptics
Non-Destructive Robotic Assessment of Mango Ripeness via Multi-Point Soft Haptics
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通过多点软触觉对芒果成熟度进行无损机器人评估
DOI：
10.1109/icra.2019.8793956
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
F. Iida
中科院分区：
文献类型：
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作者：
Luca Scimeca;P. Maiolino;Daniel Cardin;A. P. Pobil;A. Morales;F. Iida
为了满足不断提高的新鲜产品标准和减少浪费的需要，我们设计了一种替代方法，以取代破坏性和高度可变的水果成熟度估计。我们提出了一种全自动的方法来评估芒果的成熟度，这种方法是非破坏性的，允许用户用一次触摸来测试多个表面区域，并且能够在成熟和不成熟的水果之间进行分离。一个定制的夹具配备了电容式触觉传感器阵列用于触诊水果。通过简化的弹簧模型提取芒果硬度来估计成熟度。我们测试的框架上的一组25个芒果的Keitt品种，并比较结果的温度计测量。我们表明，它是可以正确地分类88%的芒果，而不删除水果的皮肤。该方法可以作为一种有价值的替代非破坏性水果成熟度检测。据作者所知，这是第一个基于电容触觉传感技术的机器人成熟度估计系统。
To match the ever increasing standards of fresh products, and the need to reduce waste, we devise an alternative to the destructive and highly variable fruit ripeness estimation by a penetrometer. We propose a fully automatic method to assess the ripeness of mango which is non-destructive, allows the user to test multiple surface areas with a single touch and is capable of dissociating between ripe and non-ripe fruits. A custom-made gripper equipped with a capacitive tactile sensor array is used to palpate the fruit. The ripeness is estimated as mango stiffness extracted through a simplified spring model. We test the framework on a set of 25 mangoes of the Keitt variety, and compare the results to penetrometer measurements. We show it is possible to correctly classify 88% of the mango without removing the skin of the fruit. The method can be a valuable substitute for non-destructive fruit ripeness testing. To the authors knowledge, this is the first robotics ripeness estimation system based on capacitive tactile sensing technology.