SWARM INTELLIGENCE BASED MAPPING AND INTRUSION DETECTION SYSTEM IN A DYNAMIC ADVERSARIAL ENVIRONMENT

Abstract

Practical swarm robotics is relatively a new field of artificial intelligence that involves small multipurpose robots capable of self-healing and dynamic task allocation. We propose an efficient swarm based mapping and intrusion detection system capable of self-healing and dynamic task allocation. Swarm based robotics is actually an inspiration from the nature. Therefore, they may as well be considered as one of the most efficient ways of handling multi-robot systems. Over time a lot of research has gone into developing and deploying multi-agent systems. We intend to maximize the efficiency of the swarm by optimizing the network, power consumption, time delays and by employing distributed computing principles in our swarm. Therefore reducing the turnaround time, computational delays and maximizing the throughput. The system may be used in hostile environments for mapping where human life may be endangered otherwise. Likewise intrusion may as well be detected in sensitive areas using this system thus reducing the manpower otherwise employed for security purpose.