Information-Driven Team Collaboration in RoboCup Rescue

Efficient collaboration in multi-robot systems (MRSs) is essential for handling complex tasks in dynamic environments under physical constraints. This study employs the RoboCup Rescue Simulation (RCRS) platform, which supports programmable rescue agents in disaster response scenarios, to investigate collaborative strategies for MRS. The proposed approach integrates a task modeling framework into RCRS to enable systematic task decomposition and coordinated request handling among platoon agents. A dedicated communication protocol further allows agents to share and exploit information dynamically in changing conditions. Experiments demonstrate simulation performance improvements ranging from 12% to 48% over default agents across complex map configurations. Results highlight the effectiveness of structured multi-agent system (MAS) collaboration mechanisms when adapted to practical physical constraints, indicating strong potential for enhancing cooperative performance in real-world multi-robot applications.