Abstract
This paper presents a system in which mobile manipulators and transport agents cooperate to solve a multi-agent pickup and delivery (MAPD) problem. The primary objective is to allocate appropriate tasks to heterogeneous robots by considering their capabilities and states. Unlike previous studies that focused on homogeneous teams or assigned distinct roles to heterogeneous robots, this work emphasizes synergy through cooperative task execution. A key feature of the proposed system is that mobile manipulators behave differently depending on whether they are paired with a transport agent. Additionally, rather than generating a full trajectory from start to end, the system plans partial trajectories, allowing dynamic re-pairing of transport agents through an auction algorithm. After re-pairing, new starting nodes are defined, and the following trajectory is updated accordingly. The proposed system is validated through simulations, and its effectiveness is demonstrated by comparing it against a baseline system without dynamic pairing.