Bio-inspired Group Modeling and Analysis for Intruder Detection in Mobile Sensor/Robotic Networks

Abstract

Although previous bio-inspired models have concentrated on invertebrates (such as ants), mammals such as primates with higher cognitive function are valuable for modeling the increasingly complex problems in engineering. Understanding primates' social and communication systems, and applying what is learned from them to engineering domains is likely to inspire solutions to a number of problems. This paper presents a novel bio-inspired approach to determine group size by researching and simulating primate society. Group size does matter for both primate society and digital entities. It is difficult to determine how to group mobile sensors/robots that patrol in a large area when many factors are considered such as patrol efficiency, wireless interference, coverage, inter/intragroup communications, etc. This paper presents a simulation-based theoretical study on patrolling strategies for robot groups with the comparison of large and small groups through simulations and theoretical results.