Cooperative transport in unknown environment - application of real-time task assignment

This paper deals with a task-assignment architecture for cooperative transport by multiple mobile robots in unknown environment. The planner should satisfy three features: to deal with the variety of tasks in time and space; do deal with a large amount of tasks; and to decide behavior in real-time. The authors (1999) have proposed the following approach: 1) based on sensor information, tasks will be dynamically generated using task templates; 2) generation of task is tuned in quality by feeding back executed result and in the number by action suppression; 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. In this paper, we implement our task-assignment architecture on a real robot system and verify the effectiveness of the proposed method by cooperative transport experiment in unknown environment.