AI Based Warehouse Management System

Abstract

Efficient warehouse management is a crucial factor for optimising the complex logistics and supply chain operations of modern industries. Even though there has been significant advancement in automation and optimization, there is a noticeable gap in research when it comes to addressing the complex challenges of adapting and ensuring the secure transportation of goods in warehouses. This research paper presents an innovative solution to bridge this gap, offering a comprehensive approach that integrates Artificial Intelligence(AI), Ant Colony optimization(ACO), robotic arm integration and ultrasonic sensor for obstacle detection for the efficiency of obstacle detection and safer goods transportation. Traditional warehouse management systems often depend on static vehicle control strategies which result in suboptimal resource utilisation and occasional collisions in the warehouse. To comprehensively address these challenges, our system integrates AI and ACO principles to optimise vehicle routing paths, thus minimising travel time. A unique feature of our approach is to include an ACO algorithm to facilitate adaptive vehicle speed control, ensure safe warehouse floor navigation and avoid collision with both stationary and moving objects Moreover, our system integrates a robotic arm into the warehouse environment, which includes flexibility in material handling. In addition this enhances the overall efficiency and adaptability of warehouse operation with evolving demands in modern industries. This research paper presents a solution to contemporary warehouse management challenges utilising AI, ACO and ultrasonic sensors for obstacle detection and robotic arm integration. The adaptive speed control mechanism optimises the vehicle route and provides the safety of goods.