Temnothorax albipennis migration inspired semi-flocking control for mobile sensor networks

Abstract

Mobile sensor networks (MSNs) are utilized in many sensing applications that require both target seeking and tracking capabilities. Dynamics of mobile agents and the interactions among them introduce new challenges in designing robust cooperative control mechanisms. In this paper, a distributed semiflocking algorithm inspired by Temnothorax albipennis migration model is proposed to address the above issues. Mobile agents under the control of the proposed semiflocking algorithm are capable of detecting targets faster and tracking them with lower energy consumption when compared with existing MSN motion control algorithms. Furthermore, the proposed semiflocking algorithm can operate energy-efficiently on both flat and uneven terrains. Simulation results demonstrate that the proposed semiflocking algorithm can provide promising performances in target seeking and tracking applications of MSNs. [More from published article abstract on publisher web] Mobile sensor networks (MSNs) can be cost effective tools for detecting and tracking moving targets in outdoor environments. However, there are issues stopping them from being widely adopted in real-world applications, including undesirable sensing performances and high energy consumption due to poor coordinations among mobile agents. This paper introduces a bio-inspired distributed coordination algorithm, which mimics the collective behaviors, known as flocking and antiflocking in animals, and the migration mechanism found in an ant species called Temnothorax albipennis (T. albipennis). The proposed semiflocking algorithm helps agents to coordinate themselves and to autonomously seek and track targets within the areas of interest (AoIs). Mobile agents under the control of the proposed semiflocking algorithm can efficiently track multiple targets in different terrains under tests. MSNs with the proposed semiflocking can detect and track down targets faster and yield a lower energy consumption due to movements of agents.