Discrimination and tracking of individual agents in a swarm of robots

Multi-agent robotic systems utilizing one-to-one communication between individuals necessarily require that each robot has a unique identity, such that shared information is appropriately utilized. When used with a central computer and external vision system, various methods may be used to identify individuals, including unique patterns. This requires a priori knowledge of the patterns, while taxing the vision system. Such methods are discussed along with their limitations. An alternative method is proposed to alleviate the strain on the vision system, eliminating the need for prior knowledge of individual patterns.