Task-oriented multi-robot learning in behavior-based systems
Parker, L.E.
Intelligent Robots and Systems apos;96, IROS 96, Proceedings of the 1996 IEEE/RSJ International Conference on
Volume 3, Issue , 4-8 Nov 1996 Page(s):1478 - 1487 vol.3
Digital Object Identifier 10.1109/IROS.1996.569009
Summary:A large application domain for multi-robot teams involves
task-oriented missions, in which potentially heterogeneous robots must
solve several distinct tasks. Previous research addressing this problem
in multi-robot systems has largely focused on issues of efficiency,
while ignoring the real-world situated robot needs of fault tolerance
and adaptivity. This paper addresses this problem by developing an
architecture called L-ALLIANCE that incorporates task-oriented action
selection mechanisms into a behavior-based system, thus increasing the
efficiency of robot team performance while maintaining the desirable
characteristics of fault tolerance and adaptivity. We present our
investigations of several competing control strategies and derive an
approach that works well in a wide variety of multi-robot task-oriented
mission scenarios. We provide a formal model of this technique to
illustrate how it can be incorporated into any behavior-based system
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