The M-POD architecture will be designed with an off-line component that defines and designs an optimal and nominal mission plan, and an online component that assists in overcoming any off-nominal conditions resulting from trajectory reshaping and retargeting. Another important outcome of this effort is the advancement in technology for real time on-line trajectory solution under feasibility constraints. The COPB functions facilitate implementation of boundary and in-flight constraints and the dynamic inversion approach allows for the solving of a set of algebraic equations that strictly satisfy the non-linear differential equations of motion. Our recent investigations have demonstrated that a combination of dynamic inversion and smooth trajectory functional representation using COPB functions provides a powerful technique for the fast computation of feasible trajectories for a dynamic system.

The primary benefit of this product is the development of technology that drastically reduces the turn around time for mission planning. What previously took months of planning, will be accomplished within a couple of hours. Trajectory generation for an autonomous system is a relatively novel field that is still undergoing research and development. Technology for real time trajectory generation and path planning is sought for a number of applications of autonomous vehicles, such as reconnaissance, search and rescue, patrolling, and ad hoc communication relay centers. M-POD will develop generic algorithms that can be easily used for various autonomous systems such as RLVs, Space Access Vehicles, uninhabited aerial vehicles (UAVs), ground vehicles (UGVs), underwater vehicles (UUVs), surface vehicles (USVs).

This material is based upon work supported by the United States Air Force under Contract No. FA8650-06-M-3637.  Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Air Force.