The goal of this initiative, funded by the Air Force and Wright-Patterson Air Force Base, was to develop a novel, radical approach for mission planning and operation that uses principles of dynamic inversion and constraint orthogonal polynomial basis (COPB) functions for solving a two-point boundary value problem for a non-flat (under-actuated) non-linear differential equation of motion. The Mission Planning and Operation Director (M-POD) for Space Access Vehicles technology allowed mission planners to prepare a complete mission plan in a matter of hours instead of months.
The M-POD architecture was 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 re-targeting. Another important outcome of this effort was 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 investigations 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 was the development of technology that drastically reduces the turn around time for mission planning. What previously took months of planning will, with M-POD, 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 develops generic algorithms that can be easily used for various autonomous systems such as RLVs, Space Access Vehicles, and uninhabited aerial vehicles (UAVs), ground vehicles (UGVs), underwater vehicles (UUVs), and 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.