Luke Baker, Chandi Sharma, Shaurya Sen, Michael Novitzky, Kristin Giammarco, Pamela Dyer, John James, Robert Semmens, Michael Collins, Stuart Harshbarger
KEYWORDS: Robots, Data modeling, Systems modeling, Modeling, Defense and security, Coastal modeling, Computing systems, Visual process modeling, Robotics, Analytical research
The Aquaticus capture-the-flag (CTF) game1, 2 was created several years ago at the Massachusetts Institute of Technology (MIT) as a testbed for human-robot teaming experiments utilizing maritime robots controlled by the MOOS-IvP autonomy stack3, 4 and humans in motorized kayaks. Monterey Phoenix (MP)5 is an open-source program for scope-complete behavior modeling created at the Naval Postgraduate School. Our objective in the work presented in this paper is to create an interface between MP logical (discrete-event) behavior models, which are text script files, and the MOOS-IvP autonomy stack used for investigating continuous-time maritime robot autonomy, including complex behaviors such as automatic collision avoidance. These physical robot behaviors are achieved by the MOOS-IvP application by generating an appropriate stream of Helm behaviors at a repetition rate of four commands a second (speed and azimuth values) by approximate solution of nonlinear differential equations. We developed a tool that extracts relevant data from the Monterey Phoenix model in JSON format and then generates an IvP Helm behavior tree, allowing for simulations of robot behavior in the MOOS-IvP environment. The results of this research can be expanded upon in the future to allow interfacing between Monterey Phoenix and other simulation environments as well as to be used in reinforcement learning environments to generate AI/ML-enabled agents to either play the CTF game in a virtual environment or to be downloaded into robots to play the CTF game live at the multi-domain operations (MDO) Human-Robot Teaming Sandbox (MDO-HuRT-S) at the United States Military Academy.
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