Design and Development of an Affordable AI-Enabled Warehouse Robotic System

Abstract

Warehouse automation technologies have significantly improved operational efficiency in large logistics centers; however, their high implementation cost often limits adoption by small scale industries and warehouse owners. This paper presents a low cost, AI enabled autonomous warehouse robotic system designed specifically for resource constrained warehouse environments. The system receives user-defined item names and quantities through a wireless interface and maps them to predefined storage locations using a microcontroller, eliminating the need for expensive real time localization and object-searching techniques. The robot navigates autonomously using an infrared (IR) sensor array that follows black line paths with cross markers for row identification. Shelf access is achieved through predefined turns, while a motor driven forklift mechanism and linear actuator retrieve baskets from different storage levels. To maintain affordability while ensuring accuracy, Husky Lens based AI is employed solely for item detection and quantity verification within the retrieved basket*. A SCARA robotic arm performs precise pick and place and sorting operations using simple inverse kinematics. The robot optimizes item retrieval by sequentially processing the nearest required items and automatically returns to the packing station upon task completion. The proposed system reduces human intervention, improves picking accuracy, and enhances operational efficiency, offering an affordable and practical warehouse automation solution for small and medium enterprises.