Abstract
With the introduction of Industry 4.0, automation and robotics have made great strides, enabling
enterprises to improve their manufacturing processes for increased productivity and efficiency. This project
introduces a novel method for implementing Industry 4.0 concepts through color-based object sorting employing
a robot arm with real-time object identification capabilities. Creating a reliable and effective system that can
automatically categorize items based on their color properties is the main goal of this project. To enable seamless
object recognition and manipulation in real time, the suggested system integrates robotic manipulation with
computer vision algorithms. The system makes use of a convolutional neural network (CNN) for precise object
detection, using recent advancements in deep learning and image processing, allowing the robot arm to interact
with a variety of items effectively. The training phase and the sorting phase are the two key phases of the
approach. The CNN model is trained on a sizable dataset of labeled objects during the training phase to recognize
various colors and forms. In order for the robotic arm to recognize things as they go along the conveyor belt and
sort them into predetermined bins according to their respective colors, the trained model must be integrated with
the robotic arm during the sorting phase. Several experiments are carried out with various lighting setups and
object arrangements to evaluate the performance of the suggested system. The outcomes show how well the
system performs in terms of exact object detection and reliable sorting. The system's capacity to effectively
handle a variety of objects and adapt to changing environmental conditions further emphasizes its suitability for
use in actual industrial scenarios. This project has important ramifications for the manufacturing sector, enabling
improved automation capabilities and cost-efficiency. An important step towards implementing Industry 4.0
principles is the seamless integration of color-based object sorting and real-time object detection using a robotic
arm. This will allow industries to optimize their production processes, minimize human intervention, and
increase overall productivity. Further developments in robotics and computer vision are anticipated to push the
limits of automation and open the door for more advanced and intelligent industrial systems as technology
develops.
Publisher
Arts and Science Press Pte. Ltd.
Cited by
1 articles.
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