GBL’s Awarded Navy SBIR Phase III to Develop and Apply Artificial Intelligence and Machine Learning Techniques for Next-Generation Mission Planning

January 2017

AI, and various versions of ML, have been applied to many fields such as cancer research, complex games like Jeopardy, Poker, and GO, and more recently heart attack prediction with great success [Ref 1]. These techniques have begun to be investigated and researched related to the topic of mission planning, as discussed at a recent conference, Tactical Advancement for the Next Generation (TANG). This SBIR topic focused on demonstrating how AI and ML could be applied to multi-vehicle, multi-domain mission planning.

Mission and strike planning are complex processes, integrating specific performance characteristics for each platform into a comprehensive mission. The Joint Mission Planning System (JMPS), a software application, consists of a basic framework and unique mission planning environment software packages for each platform.

GBL was subsequently awarded a SBIR Phase III to Develop an approach to exploit artificial intelligence (AI) and machine learning (ML) techniques (e.g., deep learning [DL]) to improve mission planning capability, and to provide autonomous and dynamic mission and strike planning capabilities in support of manned and unmanned vehicles and weapon systems.

 

REFERENCES

  1. Hutson, M. “Self-taught artificial intelligence beats doctors at predicting heart attacks.” Science Magazine, 14 April 2017. http://www.sciencemag.org/news/2017/04/self-taught-artificial-intelligence-beats-doctors-predicting-heart-attacks