A modular simulation framework for assessing swarm search models

Abstract

The ability to utilize large numbers of unmanned systems as search agents allows the implementation of different search strategies that are not currently explored utilizing today’s search decision support and analysis tools. This thesis develops a framework in MATLAB that allows the investigation of search strategies that utilize large numbers, or a swarm, of search agents. By implementing a modular design, multiple aspects of the search, such as tactics, searcher characteristics, and target characteristics, can easily be varied and analyzed. Utilizing JMP to perform statistical analysis, future design requirements can be refined in order to advise decision makers on possible alternatives and trade spaces for optimizing swarm search performance. Numerical studies demonstrate the ability to leverage the developed simulation and analysis framework to investigate three canonical swarm search models as benchmarks for future exploration of more sophisticated swarm search scenarios.