文章基本信息

标题：Artificial Intelligence-Based Robotic Technique for Reusable Waste Materials
本地全文：下载
作者：Pravin R. Kshirsagar ; Neeraj Kumar ; Ahmed H. Almulihi 等
期刊名称：Computational Intelligence and Neuroscience
印刷版ISSN：1687-5265
电子版ISSN：1687-5273
出版年度：2022
卷号：2022
DOI：10.1155/2022/2073482
语种：English
出版社：Hindawi Publishing Corporation
摘要：Waste management is a critical problem for every country, whether it is developed or developing. Selecting and managing waste are a critical part of preserving the environment and maximizing resource efficiency. In addition to reducing trash and disposal, reusable items are predicted to be of great benefit since they lessen our dependence on raw materials. The usage of compostable trash may be expanded outside fertilizers and dung after the metallic, chemicals, and glass items have been recycled. After a good scrubbing, the glass may be broken down and remelted to create new items. Reusing waste items via garbage recovery is one of the best methods to do so. This document outlines the steps that must be taken to maximize the use of garbage. This work describes a reusable industrial robot arm for grasping and sorting things depending on the resources they contain. Gripping, motion control, and object material categorization are all integrated into a full-automation, reusable system architecture in this study. LeNet also was adjusted to classify garbage into cartons and plastics using an artificial intelligent technique, with the use of a customized LeNet model. Movement in terms of moving the robot in the most efficient way possible, the robot’s grabbing, and categorization were incorporated into the movement design process. The system’s grabbing and object categorization success rates and computation time are calculated as metrics for evaluation.