Coordination and learning in multirobot systems

Finding methods for generating coherent, robust, useful and adaptive behavior in groups of autonomous robots is an increasingly active area of research. The incremental approach to robotics-first studying control and learning in a single robot-is not sufficient or even relevant (for some problems) to the multi-robot coordination and learning problem. Instead, the problem requires a general approach-which is fundamentally different from most of today's robot control and learning methods-to make the necessary strides in this challenging domain. Based on our research of situated, embodied systems, we suggest that control and learning in multi-robot systems must be addressed as a separate, novel and unified problem-not an additional "module" in a single-robot approach. We propose a bottom-up methodology to produce the desired system behavior.