Sensor placement and coordination via distributed multi-agent cooperative control

This paper examines the problem of sensor placement and coordination to maximize the sensor utilization when monitoring different types of environments. Our assumption is that the sensors are mobile and each sensor can have more than one type of sensing capabilities which can be active or not at each specific moment. The goal is to maximize the amount of information collected from the environment, given the limited amount of resources that the total of the available sensors can provide, and at the same time to be fault tolerant in failures of individual sensors by using a decentralized approach that re-organizes their placement in case of failures. We tackle this problem by employing a decentralized multi-agent coordination framework using message passing and the Max-Sum algorithm for building and maintaining a common picture of the area to be monitored. We show that by representing each sensor as an independent agent which can take decisions individually and at the same time can affect the decisions of its neighbouring sensor-agents we can provide a robust and efficient system for the monitoring of life-critical environments such as assistive environments or governmental infrastructures.