A novel automated table lookup method is developed to compute the near-fuel-optimal powered descent guidance trajectories, in real-time, for planetary soft landing. The main advantage of this algorithm is that it can be executed autonomously in milliseconds without performing iterative numerical computations to obtain the solution of the optimization problem. The key enabling idea behind this approach is to store, in a lookup table, a number of optimal trajectories that have been computed on the ground for a systematically chosen set of initial conditions. In flight, a near-fuel-optimal trajectory is computed for the actual initial condition by interpolating between these pre-computed trajectories. The lookup method requires only a small, predetermined number of basic algebraic operations. Moreover, this method guarantees that the interpolated solutions are in a prescribed neighborhood of the true optimal solutions.
This research has established that the relevant powered descent guidance problems can be posed as convex optimization problems, and hence can be solved to global optimality in polynomial time by using the interior point methods of convex optimization (CO). This property of the CO guarantees that an optimal trajectory to the target can always be computed when the target is physically reachable. Now the new automated table lookup method will enable this optimization to be preformed onboard the spacecraft very quickly and reliably in real time. In the case of planetary pinpoint landing, this onboard trajectory generation capability will be necessary to improve the landing accuracy to a few hundred meters, which is a major leap forward in the state-of-the-art.
This work was done by Behçet Açıkmese and Lars Blackmore of Caltech for NASA’s Jet Propulsion Laboratory. For more information, see: http://www.google.com/patents/US20100228409.
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Refer to NPO-47007.