Teamwork Coordination for Realistically Complex Multi Robot Systems ABSTRACT

In this paper we examine human tasks in controlling UAV teams by considering their computational complexity in the number of UAVs. This analysis suggests that controlling or following fine grained cooperation among many subteams of UAVs is the most difficult task and probably beyond human capabilities for most sizes of teams. We introduce Machinetta, a teamwork system that automates fine grained level of cooperation through proxies and uses a heuristic approach based on small world networks to allow coordination of large teams. We describe an interface based on the FalconView pfps system that has been successfully used to control small teams of UAVs. We describe likely obstacles to human control of larger teams and introduce a 3 tiered architecture in which a commander performs O(1) control tasks, a group of secondary operators perform O(n) control tasks on a call room basis, and a teamwork system such as Machinetta automates the O(mn) coordination tasks. Effective military use of robotics will depend on coordination of large teams. Automating an aircraft squadron, for example, would not only require automating the piloting of planes but also leadership functions, support roles, and incidental forms of cooperation such as battle damage assessment or escort functions. To illustrate anticipated scales one scenario proposed by RAND [1] using LOCAAS (low cost autonomous attac