Non-destructive robotic sorting of cracked pistachio using deep learning

Abstract

Pistachio, an agricultural product, is considered one of the guilt-free snacks due to its nutritional content, taste, and its health benefits. Usually, when it is consumed as a snack, in-shell pistachios are more desirable, whereas pistachios without their shell are ordinarily used for food preparation. One parameter important for pistachios sold as a snack is whether their shell is open. In pistachio processing plants, closed-shelled pistachios are separated with manual labor. There also exists an automated method called pin-picker machines, but as these machines harm pistachio kernels, they are undesirable. This paper offers a method to separate open-shelled pistachios from closed-shelled pistachios in an unharmful method. This method is done by using a deep learning-based object detection algorithm. In order to sort pistachios physically, a gripper and a conveyor system equipped Cartesian manipulator has been developed. In addition, a double-camera configuration is used. The key function of a double-camera configuration is to see the one-sided split on pistachios, which is hard to achieve with a single-camera configuration. Firstly, the object detection algorithm detects pistachios and gives their position with bounding boxes. Then their real-world coordinates are calculated, pistachios in both images taken with the cameras are paired, and the Cartesian manipulator separates pistachios. The detection accuracy was found as 98 % and 85 % for open-shelled pistachio and closed-shelled pistachio, respectively. With this method, closed-shelled pistachios can be sent to a cracking machine, or they can be sent to be stored for later use as they can withstand environmental effects better than open-shelled pistachios.