Computationally-Efficient Large Divert Guidance

To address the challenge of computational complexity in entry, descent, and landing guidance algorithms, I will develop efficient methods to compute large diverts at a distance at least twice the height at powered descent start, while respecting all spacecraft constraints and minimizing fuel consumption. Current technologies can compute constraint-satisfying and fuel-optimal diverts but these methods can only be applied to problems with linear state constraints. In addition, current guidance solutions to problems larger than 1000 solution variables are computationally infeasible on flight processors. My work will mitigate these challenges by developing a near-term implementable guidance algorithm capable of solving the fuel-optimal solution for large diverts, as well as develop algorithms for future missions requiring time-varying constraints and complex maneuvering. Near-term development will focus on reducing the computational costs of the Interior Point Method for solving multi-constrained optimization problems. The algorithm will be implemented optimally and tested on a flight computer in a high Earth altitude, full-scale demonstration. Results from the full-scale demonstration and simulations will be used to verify the technology for the Mars Sample Return mission. Long-term developments will include the extension of optimization methods to solve guidance problems that are currently unsolvable for a globally optimal solution. The final algorithm will be capable of autonomously maneuvering in complex, multi-agent environments. These developments in high-level autonomy will enable large diverts for pinpoint landing of the Crewed Mars Surface Mission. Research in computationally-efficient methods for solving large divert guidance problems will directly support TABS 9.2 Descent and Targeting Technologies in the NASA Technology Roadmap. The proposed project will advance large divert guidance to TRL 6 by formulating methods for solving multi-constrained optimization problems to improve runtime on current flight processors.

The proposed project will advance large divert guidance by formulating methods for solving multi-constrained optimization problems to improve runtime on current flight processors.

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