Connectivity preserving task allocation in mobile robotic sensor network

Abstract

Robotic sensor network (RSN) contains mobile sensors and robots provides feasible solution for many multiagent applications. One of the most critical issues in RSN and its application is how to effectively assign tasks. This paper presents a novel threshold-based task allocation strategy to answer the question particularly for RSN. Firstly, we model the task allocation in RSN to distinguish the discovering and allocating processes. Secondly, a fully distributed simple Threshold-based Unoccupied Neighbor Algorithm, namely TUNA, is developed to allocate tasks with only partial view of the network topology. A connectivity controller is finally developed and integrated into the strategy to guarantee the global connectivity of entire RSN, which is critical in most RSN applications. Experimental simulations are also provided to evaluate the performance of the proposed strategy.