Probabilistic Aggregation Strategies in Swarm Robotic Systems
Soysal Onur, Sahin Erol

Abstract:

In this study, a systematic analysis of probabilistic aggregation strategies in swarm robotic systems is presented. A generic aggregation behavior is proposed as a combination of four basic behaviors: {\em obstacle avoidance}, {\em approach}, {\em repel}, and {\em wait}. The latter three basic behaviors are combined using a three-state finite state machine with two probabilistic transitions among them. Two different metrics were used to compare performance of strategies. Through systematic experiments, how the aggregation performance, as measured by these two metrics, change 1)~with transition probabilities, 2)~with number of simulation steps, and 3)~with arena size, is studied.