Demonstration of a Distributed Cooperative Strategy Planning Algorithm in a Multi-Agent System with Multiple Objectives

Robot-based services are increasingly being integrated into everyday life. In the diverse environments in which humans live, systems are expected to respond to dynamically changing surroundings by enabling distributed control and cooperation. However, in spaces where various robots coexist, it is practically challenging to ensure that all robots in the space can communicate all necessary information with one another. This poses challenges related to communication failures, the need for unified communication standards, and legal regulations for robots that do not comply with these standards. Furthermore, from the perspective of coexistence with robots in urban areas, there are many entities, such as humans, birds, and cats, with which standardized communication is not feasible. When introducing robots into environments such as cities, it is necessary to share pathways such as roads, sidewalks, and corridors, as well as public infrastructure such as buses and trains, with non-communicating entities. Therefore, in the social application of such robots, it is desirable to construct a system that can operate on the premise that it cannot obtain complete information about other robots or living organisms, and it is necessary to consider a system that can continue its mission even when information about other robots is ambiguous. In this study, we investigated a distributed cooperative strategy planning algorithm for a multi-agent system with multiple tasks of patrolling three designated points specified by coordinates in an unknown space. The algorithm assigns tasks to each agent and enables the system to continue its mission even when agents cannot accurately obtain information about one another. We also verified the effectiveness of this algorithm using actual robots and report the results.