Adaptive Cooperative Path and Mission Planning for Multiple Aerial Platforms

Path planning and mission planning are two core steps to effectively exploit the capabilities of multi-level cooperative control of multiple aerial platforms. In this proposal, Intelligent Automation, Inc. (IAI) and its subcontractor, Prof. Jose B. Cruz of the Ohio State University, propose to develop innovative algorithms and software tools that are built on a hierarchical game-theoretic framework to automate path planning and mission planning for multiple unmanned platforms to enhance system effectiveness and robustness. The mission planning is formulated as a non-cooperative non-zero-sum game and a co-evolutionary algorithm is proposed for calculating the Nash strategies for target assignment. Cooperative path planning is formulated in the framework of Pareto optimization and its solution would serve as a reference trajectory for Foraging algorithm. Essential to the framework is the networked communication and intelligence for sharing real-time data among the command facilities and the individual platforms. Real time information for target or threat locations before and during engagements may necessitate re-plan of path and mission.