Advanced Flocking Control Algorithms in Mobile Sensor Networks

Abstract

Mobile sensor networks (MSNs) have been facilitating many applications in different fields for both event detection and data collection purposes. Sensors are attached in mobile robots or vehicles to sense, measure or to detect events based on specific applications. Flocking control algorithm have been developed and applied in leading robots in sensing areas to detect or to build scalar maps. The group of robots or mobile sensors connect to each other based on a communication. All the mobile sensors need to maintain their connections all the time while working in the field. Due to the energy limitation, the sensors have limited communication range that cannot guarantee that the school of sensors connected all the time. This work proposes a new method to overcome the problem by using a data processing method, called Compressed sensing, that allows the mobile sensors can be separated sometimes and still can collect all sensing data needed to build a scalar map at each distributed mobile sensor. In addition, simulation and experimental results are provided to clarify the algorithm.