Minimizing complexity in controlling a mobile robot population

The author addresses the problem of distributing a task over a collection of homogeneous mobile robots. In contrast to hierarchical methods, which assign a leadership hierarchy and a priori roles to different robots, the proposed approach attempts to detect and utilize the run-time group dynamics within the robot collective. The authors apply a distributed control approach both on the level of the individual robot and on the level of the colony. This choice involves a number of tradeoffs. The complexity of a traditional centralized planner is replaced by the complexity of inter-robot and inter-behavior dynamics. The authors explore methods for not only overcoming interference but utilizing those dynamics to achieve super-linear improvements in task performance. They report the results of testing this architecture on a collection of homogeneous mobile robots. The robots were tested on a number of tasks with a series of more intelligent and efficient local control strategies