This project aims at developing advanced entry and powered descent guidance technology for precise planetary landing. A human- mars mission requires the delivery of a high payload from the entry…

This is a grant awarded by the National Aeronautics and Space Administration (NASA) to The Ohio State University on October 1, 2018 for $339,844.59 to develop advanced entry and powered descent guidance technology for precise planetary landing. The goal is to optimize end-to-end entry, descent, and landing (EDL) trajectories in real-time to enable fuel-optimal and precise landing for future human-scale Mars missions. The project aims to advance modeling, optimization, and simulation capabilities to achieve this, with a target of maturing the technology from Technology Readiness Level 1 to 3 by the end of the 24-month period of performance. No set-aside was used for this research grant.

This project aims at developing advanced entry and powered descent guidance technology for precise planetary landing. A human- mars mission requires the delivery of a high payload from the entry interface at a hypersonic speed to a preflight-designated surface location at near-zero speed with pinpoint precision. The supersonic retro-propulsion system required to decelerate a human-scale vehicle consumes significant amount of propellant. IT becomes a challenging task to achieve high precision landing while minimizing fuel consumption during the powered descent phase. Moreover, the multi-phase operation (entry, descent, and landing), nonlinear vehicle dynamics, and mission constraints make IT even more challenging to generate onboard fuel-optimal guidance maneuvers to accomplish the mission. The goal of this project is to develop a highly implementable guidance approach that optimizes the end-to-end complete entry, powered descent, and landing (EDL) trajectories in real-time to achieve the fuel-optimal and precise landing. In pursuit of this goal, three essential research objectives will be investigated, including (1) developing high fidelity and computationally efficient mission models with both conventional bank-angle control and direct-force control maneuvers for entry flight, (2) designing a fast converging online optimization algorithm based on advanced computational techniques, and (3) conducting virtual simulation and experimental verification, which will jointly contribute to the advances of fuel-optimal entry and descent guidance algorithms to enable precise landing. The end-to-end onboard optimal mission planning is the first attempt to solve multiphase guidance problems as an entire mission based on a robust and scalable optimization algorithm. The approach will start with a new modeling paradigm that unifies mathematical representations of both entry and powered descent guidance problems integrating vehicle dynamics in each phase, trajectory and operational constraints, and landing precision requirements. This unique model will incorporate direct control of aerodynamic forces in entry flight through modulations of angle of attack and sideslip angle to achieve advanced mobility. A three-degree-of-freedom model based on spherical elements will be constructed first and then expanded to a six-degree-of-freedom model based on dual quaternions considering coupled translational and rotational motions. The onboard mission planning scheme aims to optimize the entire EDL trajectory as a whole, including designing simultaneously optimal maneuvers in each phase and selecting an ideal initiation of powered descent. To overcome the computational bottleneck in solving large-scale nonconvex optimization problems, the optimization algorithm will leverage breakthroughs in matrix decomposition, alternating minimization, and cutting plane methods to achieve scalability and robust convergence. The proposed modeling and optimization method will be evaluated via monte carlo simulation, implementation in an experimental testbed, and final assessment in NASA flight simulations. All these efforts will eventually push the technology from the starting TRL 1 to TRL 3 at the end of the project.