A proactive risk-aware robotic sensor network for Critical Infrastructure Protection

Jamieson McCausland, George Di Nardo, Rafael Falcon, Rami Abielmona, Voicu Groza, Emil Petriu
2013 2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA)  
In this thesis a Proactive Risk-Aware Robotic Sensor Network (RSN) is proposed for the application of Critical Infrastructure Protection (CIP). Each robotic member of the RSN is granted a perception of risk by means of a Risk Management Framework (RMF). A fuzzy-risk model is used to extract distress-based risk features and potential intrusion-based risk features for CIP. Detected high-risk events invoke a fuzzy-auction Multi-Robot Task Allocation (MRTA) algorithm to create a response group for
more » ... ach detected risk. Through Evolutionary Multi-Objective (EMO) optimization, a Pareto set of optimal robot configurations for a response group will be generated using the Non-Dominating Sorting Genetic Algorithm II (NSGA-II). The optimization objectives are to maximize sensor coverage of essential spatial regions and minimize the amount of energy exerted by the response group. A set of nondominated solutions are produced from EMO optimization for a decision maker to select a single response. The RSN response group will re-organize based on the specifications of the selected response. ii
doi:10.1109/civemsa.2013.6617409 fatcat:uoae5y4eurcotcpaivndgiwo4i