The proposed solution focuses on the centralized monitoring and navigation control of a swarm of mobile robots, leveraging a modified SLAM (Simultaneous Localization and Mapping) algorithm to improve operational efficiency in automated package handling. The system architecture integrates multiple components, including a multi-camera interface, a centralized CPU for swarm coordination, a 3-axis gantry system for package sortation and storage, and a 4-axis SCARA robot to manage the pick-and-place operations between the Automated Storage and Retrieval System (ASRS) and the mobile robots.

Each customized swarm robot is a 4-wheeled platform, controlled wirelessly via an ESP32 microcontroller module using Wi-Fi communication. These robots are equipped with an automatic package delivery mechanism driven by servo-actuation techniques. The overall system operates on the Robot Operating System (ROS) platform, which enables seamless integration and interoperability of various subsystems through Modbus communication protocols.

Traditionally, SLAM algorithms rely on sensor fusion methods combining data from LIDAR, IMU (Inertial Measurement Unit), wheel encoders, and optical sensors to achieve accurate localization and mapping. The proposed system introduces a modified SLAM algorithm that enhances positional awareness by incorporating ARUCO marker detection techniques, utilizing the OpenCV library. This approach provides improved precision in determining the robots' position and orientation within the workspace.

Furthermore, the system employs image processing techniques to analyze the color of the packages, which assists in dynamically assigning delivery destinations based on color-coded identification. The vision system plays a critical role in real-time monitoring, using camera feeds to detect the instantaneous locations of multiple swarm robots. It continuously evaluates the likelihood of collisions and dynamically generates alternative navigation paths to ensure smooth and safe movement toward designated destinations.

A robust recovery mechanism is embedded within the navigation algorithm to handle scenarios where a robot encounters obstacles or becomes immobilized. If a robot remains idle despite receiving continuous velocity commands, the system activates a recovery behavior that guides the robot back to a previously known safe path, thus enhancing overall reliability.

Key features of the proposed navigation algorithm include effective collision avoidance, dynamic obstacle management, and intelligent recovery behaviors, ensuring efficient and autonomous operation in complex environments. By addressing major limitations identified in the problem statement—such as collision risks, navigation inefficiencies, and coordination challenges—the proposed system offers a scalable and adaptable solution.

While the system performs effectively, it does exhibit minor latency issues, which could be mitigated by integrating high-end GPUs to further enhance processing speed and responsiveness. Overall, this solution provides a promising approach to advancing the automation of package handling and delivery through intelligent swarm robotics.