Adaptive action selection without explicit communication for multirobot box-pushing

The paper describes a novel action selection method for multiple mobile robots box-pushing in a dynamic environment. The robots are designed to need no explicit communication and be adaptive to dynamic environments by changing modules of behavior. The various control methods for a multirobot system have been studied both in centralized and decentralized approaches, however, they needed explicit communication such as a radio, though such communication is expensive and unstable. Furthermore, though it is a significant issue to develop adaptive action selection for a multirobot system to a dynamic environment, few studies have been done on it. Thus, we propose action selection without explicit communication for multirobot box-pushing which changes a suitable behavior set depending on a situation for adaptation to a dynamic environment. First, four situations are defined with two parameters: the existence of other robots and the task difficulty. Next, we propose an architecture of action selection which consists of a situation recognizer and sets of suitable behaviors to the situations and carefully design the suitable behaviors for each of the situations. Using the architecture, a mobile robot recognizes the current situation and activates the suitable behavior set to it. Then it acts with a behavior-based approach using the activated behaviors and can change the current situation when the environment changes. We fully implement our method on four real mobile robots and conduct various experiments in dynamic environments. As a result, we find out our approach is promising for designing adaptive multirobot box-pushing.