SCAN: A Sensor Deployment Algorithm in Hazardous Regions via Mobile Actuators

Abstract

In this paper, we propose two novel robot-assisted energy-efficient wireless mobile sensor deployment algorithms to monitor hazardous, uneven, and obstacle-prone areas where human intervention is prohibited. The algorithms are designed to exploit the operation in two simple steps. Initially, the robot deploys the mobile sensors in suitable positions by exploring the intended region using two different methods: 1) basic SCAN 1 and 2) opportunistic SCAN. In basic SCAN, the robot explores the intended area using simple scanning to install sensors. On the other hand, in opportunistic SCAN, the robot explores the intended area and installs the sensors whenever possible and stays in that region to cover as much as it can. Then, the installed sensors run coverage algorithm to provide information about the empty neighborhood to the running robot. Initially, the robot starts from some reference point and deploys sensors avoiding any obstacles or boundaries without the help of GPS. Combining these algorithms with the coverage algorithm guarantees maximum coverage for different obstacle distributions and for different regions of interest. Extensive simulation experiments are conducted to evaluate these algorithms. Opportunistic SCAN algorithm provides maximum coverage with minimum travel distance for the robot compared with the basic SCAN algorithm and the backtracking algorithm. Our algorithm also eliminates the deadlock issue for the robots that is raised when back pointer is removed. 1 Scalable Coordinate Accumulation Network.