Efficient Battery Management and Workflow Optimization in Warehouse Robotics through Advanced Localization and Communication Systems

This study introduces a prototype of the Warehouse Robot Localization and Communication System designed to optimize battery management and maintain an uninterrupted workflow in warehouse environments. The system includes autonomous mobile robots equipped with advanced localization and wireless communication technologies. When a robot currently assigned a task has its battery level drop below a predefined threshold, it communicates with the main computer via Wi-Fi to request assistance. An available robot then adjusts its task, navigating the shortest path to the low-battery robot's location, guided by a webcam system. Then, the low-battery robot proceeds to a charging station after transferring its task to the arrived assisting robot. The study aims to enhance productivity by reducing downtime through efficient battery management, precise localization, reliable communication, and a user-friendly control interface. To achieve localization, an overhead camera was used to capture a comprehensive image of the work floor. This image was processed to generate a detailed map tracing paths and obstacles. This mapping is only repeated if the work floor changes. The A* algorithm was integrated into the main controller program to ensure optimal pathfinding based on real-time data. The positions, orientations, and movements of the mobile robots were accurately tracked using color codes and their shapes. A Wi-Fi-based communication was integrated to facilitate data exchange with the main computer, including battery levels, orientation, path coordinates, and assistance requests. A Python-based user interface was designed for monitoring and controlling purposes. After implementation, the mobile robots successfully detected their battery levels, communicated with the main computer, and autonomously assigned tasks and localized themselves, effectively eliminating the need for manual intervention. This prototype system has the potential for further development into a market-ready product for industrial applications. Future work includes enhancing multitasking capabilities, incorporating additional sensors for improved accuracy, and optimizing power consumption management.