This technology enables a spacecraft to autonomously approach and maneuver around a small body of unknown physical parameters (shape and mass distribution) while simultaneously mapping the body’s geometry and gravity field as well as estimating the spacecraft’s trajectory around body. Today, this is a key challenge in spacecraft navigation during approach, which relies heavily on ground-in-loop guidance by mission operators and ground-based support tools that have stale and limited spacecraft state information due to communication delays and bandwidth limitations.
The autonomous onboard estimation of the body’s physical and dynamical parameters and the spacecraft’s trajectory constitutes a significant technological advance. Our goal is to advance the algorithmic foundations that enable simultaneous shape modeling, gravity-field estimation, orbit determination, and planning the motion of the spacecraft as it autonomously approaches a small body. We will develop the mathematical estimation formulation, implement the algorithms, and assess their performance on simulated and real images from the Rosetta mission to ensure accuracies for target-relative orbit knowledge and prediction comparable to those obtained by ground-based radiometric and optical techniques. If results prove promising, evaluate on live data from one of two upcoming missions, shadowing JPL’s navigation of Hayabusa 2 (7/18) or OSIRIS-REx (9/18). We also plan to integrate the algorithms onto Caltech’s spacecraft test bed.
The autonomous approach and maneuvering around small bodies is a foundational capability that would enable science investigations, mapping, and landing on asteroids, comets, and small moons of outer planets. By allowing onboard autonomy to handle the complex interactions among perception, navigation, and planning for the spacecraft, it frees up the science team to focus on the science investigations. Moreover, it would also enable future multi-spacecraft mission concepts to rapidly map single or multiple small bodies, providing a mission architecture with flexibility and robustness given redundant assets.
