Task-level Collaboration between Automated Guided Vehicles (AGV) for Efficient Warehouse Logistics

Automated guided vehicles (AGVs) are a key technology in current warehouse automation, driving significant increases in efficiency and cost reductions. In recent years there has been much development in robotic systems for Industry 4.0, but little research into task-level collaboration of AGVs to achieve a common goal. Collaboration of AGVs for conflict resolution and coordination is already widespread; however, few studies have investigated whether AGVs can collaborate at the task level, accomplishing work more efficiently by dividing a task into smaller subtasks. This thesis explores task-level collaboration between robots by implementing a prototype and evaluating it in a fictitious warehouse scenario, to find out whether collaborative task sharing and execution can increase efficiency and reduce delivery time. After reviewing the literature and related work, a solution is designed and a prototype built with the DJI RoboMaster EP Core robot, then tested and evaluated experimentally across several scenarios.