Behavior analysis of search and rescue operations employing human-machine teaming

Abstract

During the summer of 2022, the United States Military Academy hosted a robotics apprenticeship program during which interns programmed maritime robots to move autonomously. By the end of the apprenticeship, the robots were able to compete against each other in a force-on-force competition based on capture-the-flag game rules. This game mimics tactics performed in military operations and is used for studying new military tactics and operations involving humans and robots working with each other and in human-robot teams. The live tests were planned using Monterey Phoenix,1 a Navy-developed language, approach and tool for behavior modeling. Monterey Phoenix was used to generate a set of possible scenarios that could occur during the robot competition based on the game rules and expected conditions. Scenario variants containing search and rescue (SAR) operations were included to help with planning in case of a man overboard or robot malfunction. The analysis in Monterey Phoenix led to the exposure of some new SAR scenario variants that were not previously considered, including: the weather being unsafe but shoreside permitting continued play; two men overboard events happening simultaneously on both teams; SAR is deployed despite not being signaled to; and lastly one team has a man overboard event but the other team is unaware and continues playing the game. Having a library of these and other possible scenario variants helped the team consider possible causes for their occurrence and avoid or mitigate unwanted outcomes that could arise should they occur during live competition.