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Robust Spacecraft Guidance Incorporating High-Fidelity Uncertainty Propagation and Chance Constraints
Active
TRL 2 (started at 2, targeting 3)
Description
Spacecraft state uncertainty is a critical challenge due to the unpredictable nature of space dynamics, causing errors to accumulate over time and spacecraft to deviate from planned trajectories. Quantifying and minimizing this uncertainty over time is particularly relevant in cislunar and interplanetary regimes, where complex nonlinear dynamics play a significant role. As these system dynamics cause errors to grow over time and drive a trajectory to deviate from its planned path, corrective guidance algorithms must adaptively re-optimize the spacecraft thrust maneuvers to reach target states and achieve mission goals, such as precise science observations or strict orbit accuracy. To address these challenges, this project proposes combining guidance with efficient uncertainty propagation techniques, resulting in robust chance-constrained guidance that bounds state uncertainty rather than constraining a single deterministic state. State- of-the-art guidance will be advanced by combining stochastic control approaches to uncertainty with nonlinear, non-Gaussian chance constraints while incorporating thrust maneuver errors. This approach offers generality across applications and control methods, improving spacecraft autonomy and scientific returns for space missions in the cislunar region and planetary exploration environments. This research's extension to non-Gaussian chance constraints is better suited for missions with measurement gaps and for future state predictions. By identifying gaps in current guidance laws, incorporating chance constraints with non-Gaussian uncertainty, and applying the novel algorithm to highly dynamical test cases in cislunar and interplanetary regimes, this project accomplishes robust spacecraft guidance under uncertainty. Once formulated for onboard implementation, this algorithm allows for adaptive autonomy for spacecraft in complex dynamics and congested operating environments, which is especially relevant due to increased congestion in near-Earth and cislunar space and the planned utilization of NASA's Gateway as an outpost for new interplanetary missions.
Details
| Technology area | GN&C > Guidance and Targeting Algorithms > Guidance Algorithms |
| Program | Space Technology Research Grants (STRG) |
| Lead organization | University of Colorado Boulder, Boulder, CO |
| Start date | 2024-08-01 |
| End date | 2028-08-31 |
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