Multi-robot Task Allocation in E-Commerce Warehouses: A Comparative Analysis of Distance Minimization and Priority-Based Approaches

This paper presents a methodology for warehouse management with multiple robots for the efficient picking and dropping of consignments. Task allocation is a critical challenge in this process, as it requires determining a collision-free path for all robots based on warehouse management preferences. Two task allocation preferences are considered: (1) minimizing the total distance traveled by all robots to reduce power consumption and improve overall efficiency and (2) prioritizing task allocation by assigning tasks to the nearest available robot for faster delivery. The proposed approach uses the A* algorithm to determine the shortest path for each robot and evaluates the overall lower cost with the Kuhn-Munkres algorithm. Simulation results show the effectiveness of the methodology in achieving efficient task allocation and reducing the overall distance traveled.