Abstract
This paper deals with a task-assignment architecture for cooperative transport by multiple mobile robots in unknown environment. The architecture should satisfy three features: to deal with the variety of tasks in time and space; to deal with a large amount of tasks; and, to decide behavior in real-time. The authors propose the following approach: (1) We consider the unit of task (task instance) as the form that should be done in short time by one robot. Based on environmental information, task instances are dynamically generated using task templates; (2) Priority of task instances are evaluated dynamically based on the number of robots and the configuration in the work space. In addition, it is avoided to generate too many task instances by suppressing movement; (3) Main part of the architecture consists of two real-time planner: priority-based task-assignment planner solved by using a linear programming method and motion planners based on short-time estimation. Effectiveness of the proposed architecture is verified by a cooperative transport simulation in unknown environment.
