Paper Contents
Abstract
The increasing demands of modern logistics and manufacturing have necessitated the development of efficient and automated material handling solutions. This project focuses on the design and implementation of an autonomous forklift system utilizing a robot control framework to enhance industrial automation. The forklift is equipped with advanced sensors, including LiDAR, ultrasonic sensors, and cameras, which enable real-time navigation, obstacle detection, and load handling. One of the primary challenges in such autonomous systems is ensuring accurate and safe material handling in dynamic environments. To address this, an advanced control system has been integrated to manage pallet detection, optimize path planning, and monitor the systems overall performance. Additionally, safety protocols have been embedded to ensure collision avoidance and efficient task execution. This paper presents a detailed study of the control algorithms and sensor integration used in the system, evaluating their effectiveness in improving operational efficiency and safety. The proposed autonomous forklift system shows great potential in transforming logistics and manufacturing processes by reducing labor costs, increasing efficiency, and promoting safety in industrial environments. This review paper also briefly outlines the design, methodology, and future applications of the system, demonstrating its role in advancing smart warehouse and industrial solutions.
Copyright
Copyright © 2024 A HARRISON KEVIN RAJ. This is an open access article distributed under the Creative Commons Attribution License.
