End-to-End Trajectory Optimization

Human exploration of the Solar System is in our DNA. NASA is currently planning missions to the Moon (Artemis Program) in preparation for longer missions to Mars and beyond. These space missions are becoming increasingly complex with more and more players involved in the logistics. For instance, Artemis III will utilize Orion to get astronauts to the vicinity of the Moon, while HLS will take astronauts down to the surface. Artemis IV+ will utilize Gateway—NASA’s planned space station around the Moon—as an intermediate outpost before traveling down to the surface. Successful planning and implementation of these missions will require performance optimization and efficient utilization of resources between not only different mission design teams but also the different companies involved in development of the different vehicles. Having technology like the end-to-end mission design optimization capability will be critical to smoothing the mission design process between them, as well as finding performance benefits to save critical resources and improve mission coverage that wouldn’t be accessible otherwise

The above motivation identifies a need for a generalized, robust, user-friendly and accessible end-to-end mission design optimization tool. Our solution to developing this capability was to interface two JSC tools—Copernicus and Genesis. Copernicus is a trajectory design and optimization software used for in-space trajectories around multiple bodies. It is the backbone for Orion mission design here at JSC and is being used in all aspects of Artemis, HLS, Gateway, and PPE mission design (at several NASA centers: JSC, MSFC, GRC, and others). Genesis is another flight mechanics tool used to model ascent, entry, descent, and landing trajectories around a single planetary body. It includes a suite of atmospheric and powered flight guidance algorithms. Each of these tools has a specific area of the mission design process that it excels at. By utilizing them both, we can gain performance benefits not seen by either on their own.

Year 1 was focused on combining these 2 software packages—essentially allowing Copernicus to incorporate the ascent/descent capabilities of Genesis into the optimization problem—and developing this end-to-end mission design capability. As we were building this initial capability during Year 1, we found that the guidance within Genesis was very sensitive to initial conditions.

As a result, for Year 2 we focused on increasing the robustness of this capability by building the initial guess generator (IGG). IGG produces initial guesses based on simplifying assumptions and the physics of the problem. The idea was to build in some of the expertise of trajectory design into the IGG tool so that the user could quickly and reliably have a good starting guess when running a case. An additional benefit of developing IGG is that it enabled us to parallelize our scans, which improved the speed and convergence of our runs. Overall this tool enabled us to increase the speed, reliability, and robustness of our end-to-end mission capability.

Year 3 of our project focuses on utilizing the end-to-end mission design and optimization capabilities developed in the previous 2 years to analyze specific mission scenarios—scaling up from proof of concept to real analyses—capturing any resulting performance benefits, as well as addressing the Big Data challenges we’re faced with—namely, how we’re going to manage and interpret all the data that’s generated. For instance, Artemis I mission design generated millions of trajectories (terabytes of data), which were difficult to access and distill in a meaningful and efficient way. Strategies and tools such as Machine Learning for data management, visualization, and interpretation are needed and will be explored.

Why do we want end-to-end optimization? Traditionally, friction points exist where different mission design teams (e.g., a launch/ascent team, an on-orbit team, and a descent/landing team) all design and optimize their portion of the trajectory independently and meet at a shared handoff point, rather than optimizing the full mission profile. Our goal is to unconstrain that handoff point to not only gain performance benefits but to also improve the iterative mission design process itself. Potential performance benefits include decreased propellant usage, better abort coverage, and increased mission availability.

• Improve efficiency of the mission design process and integration of different teams. By unconstraining the handoff points between different mission design teams, this technology will improve the mission design process itself—both from a time efficiency perspective, but also from a performance efficiency perspective.

• Aid mission architecture decisions, pre-flight product development, and real-time operational support. Copernicus is already used in all aspects of Orion mission design—from pre-mission design to real-time on-console support. Utilizing the added benefits of Genesis in-the-loop with Copernicus will only improve data products used in decision making.

• Advance human spaceflight toward onboard abort autonomy. Moving towards the goal of providing astronauts the ability to design and execute aborts on their own, this technology is a necessary stepping stone. The example scenario being a crew member who has lost comm with Mission Control and needs to run this tool to come up with abort options and execute a burn back to Earth for safe return.

This is early/mid-stage (TRL 5) — the most realistic path in is NASA SBIR/STTR, which funds small businesses and research institutions to develop technology aligned with NASA's needs (equity-free, phased funding). Check whether a current SBIR/STTR solicitation topic overlaps with this project's technology area, or contact the project directly (above) to ask.

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