Adaptive Cooperative Path and Mission Planning for Multiple Aerial Platforms Navy STTR FY2004 Sol No.: Navy STTR FY2004 Topic No.: N04-T003 Topic Title: Adaptive Cooperative Path and Mission Planning for Multiple Aerial Platforms Proposal No.: N045-003-0244 Firm: Intelligent Automation, Inc. 15400 Calhoun Drive Suite 400 Rockville, Maryland 20855 Contact: Chiman Kwan Phone: (301) 294-5238 Web Site: www.i-a-i.com Abstract: 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. Benefits: The proposed cooperative path and mission planning framework has great potential in many applications. First, robust and real-time cooperative path and mission planning is very important for military unmanned platforms applications, such as UAV, UUV, UGV, and weapons. Second, many civilian applications such as robotic exploration of remote location, smart car, agriculture harvesting will need path and mission planning. Return