The Daniel Guggenheim School of Aerospace Engineering at Georgia Tech

Micro Autonomous Systems Technology

Executive Summary

Micro-Autonomous Systems and Technologies (MAST) is a research thrust from the Army Research Lab (ARL) to creat a synergistic assembly of multifunctional, mobile microsystems to enhance the Warfighter's tactical situational awareness in complex and dynamic terrain. In order to achieve this overall goal, MAST systems are designed to be collaborative, adaptive, efficient in relaying the information they accrue, small in scale, and autonomous.

Team Members

Patrick Dees
Program Manager

Prof. Dimitri Mavris
Academic Advisor

Steven Jackson
Chief Engineer

Dr. Stephane Dufresne
Technical Advisor

Brendan Andrus
Graduate Researcher

Zohaib Mian
Student Advisor

Timothy Dyer
Graduate Researcher

Leslie Hall
Graduate Researcher

Pierre Valdez
Graduate Researcher


The greatest hurdle to be faced in integrating these platforms is the requirements disconnect between Warfighter and Technologist. One one end of the spectrum, the Warfighter knows that they require intelligence, surveillance, and reconnaissance to safely and successfully execute a mission. At the other end the Technologist developing subsystems is asking questions like "What energy density do the batteries need to have?" Both of these integral components of MAST development are disconnected from one another in the scale they think of in developing MAST systems, in that the Warfighter needs useful tehcnologies, and the Technologist needs requirements to make useful systems.

An avenue for passing information important to either end of the spectrum would allow either end-user or Technologist to translate their wants and needs into a form the other can interpret and understand. However, in developing technologies, Technologists come to a roadblock in finding an analogy to existing physics in the environments they are designing for, because the arenas MAST systems operate in (Small-scale, low Reynolds number) are still relatively unexplored. Further experimentation is needed to ground system behavior in fundamental physics. Moving further through the information chain, before an adequate method of sizing & synthesis for describing integrated system behavior can be developed, models have to be created to describe this behavior, which requires experimentation to formulate said models. Before any investigation into mission effectiveness can begin, the behavior of integrated systems must be understood, once again requiring the development of models and experiments to back the models. Finally, before investigation into the behavior of swarms of MAST vehicles can begin, the same problems must be addressed. So overall the same problems occur over again in MAST development, leading to the conclusion that a scientific process is needed to facilitate integration and achieve MAST's final goal.


In order to bridge the requirements disconnect, the MAST Grand Challenge teams have developed three elements: a Techology Assessment, a Sizing & Synthesis tool, and a Modeling & Simulation (M&S) environment. From the Technologist we gather performance characteristics of experimental platforms, which yields an assessment on the current sophistication of developed & developing technologies. These performance metrics are fed into a system for Sizing & Synthesis which allows the construction of virtual vehicles within a modeling & simulation environment based upon characteristics of platforms currently existing or soon to exist. The modeling & simulation environment is grounded in information gathered from the Warfighter on mission tactics & preferences, which provides the framework for M&S. The M&S environment then outputs simulated performance of the vehicles within the environment using metrics based on currently available technologies. Comparing the performance of these vehicles against those which have the highest measures of mission effectiveness finally results in a gap analysis. In doing this comparison, the functional performance of every subsystem and the system as a whole can be addressed with regards to the entirety of the design space, allowing the construction of a system trade-space.

Once experimental and simulated performance metrics are gathered on the entire design space, analysis may yield gaps in required performance, pointing in the direction which further system development would yield the greatest returns on integrated system mission effectiveness.

Analysis and Results

This year of research primarily focused on development of the varied tools required to implement our overall research path. Therefore, the only results so far have been general trends and increasing the fidelity of simulation.

We expect that the behavior of heterogenous swarms of MAST vehicles will become an important player in succeeding years of research.