Market-based dynamic task allocation in mobile surveillance systems

Abstract

Mobile surveillance systems include a vast array of mobile sensing nodes with varying sensing modalities that can sense continuously the volume of interest. These distributed nodes are capable of sensing, processing, mobilization and communication with other nodes. One of the fundamental problems of mobile surveillance systems is how to assign a set of tasks to a set of mobile sensors and how to coordinate the behavior of these mobile sensing nodes in order to perform cooperative tasks efficiently. This problem is known as multi-robot task allocation (MRTA). This paper presents centralized and hierarchical dynamic and fixed tree task allocation approaches to solve the MRTA problem. The objective comparison results show that hierarchical dynamic tree task allocation outperforms all the other techniques especially in complex surveillance operations where large number of robots is used to scan large number of areas.