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物体分类系统采用机械臂

摘要

提出了一种用于连续流中目标的实时检测和选择的智能方法。图像处理在当今世界受到广泛关注，因为它在许多高科技领域都有广阔的应用前景。真正的挑战是如何改进现有的分拣系统的模块化处理系统，该系统由识别、处理、选择和分拣四个集成站组成，具有新的图像处理功能。现有的分选方法使用了一套电感、电容和光学传感器来区分物体的颜色。本文提出了一种应用于图像处理的机电分色系统解决方案。图像处理程序感知网络摄像头实时捕捉到的图像中的物体，然后从中识别颜色和信息。这些信息通过图像处理进行拾取和放置机制处理。排序过程基于定义为1)设备学习识别对象的自我学习步骤的2阶段操作方法;2)一个可操作的选择过程，其中对象被检测到，使用决策算法分类并实时选择。该项目涉及一个自动化物料处理系统。 It aims in classifying the colored objects by colour, size, which are coming on the conveyor by picking and placing the objects in its respective pre-programmed place. Thereby eliminating the monotonous work done by human, achieving accuracy and speed in the work. The project involve sensors that senses the object’s colour, size and sends the signal to the microcontroller. The microcontroller sends signal to circuit which drives the various motors of the robotic arm to grip the object and place it in the specified location. Based upon the detection, the robotic arm moves to the specified location, releases the object and comes back to the original position [1] [2].

Vishnu R. Kale, V. A. Kulkarni

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