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Caltech

Spacecraft Guidance and Control under Probabilistic Uncertainty for Coordinated Inspection and Safe Learning

Friday, April 30, 2021
3:00pm to 4:00pm
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Online Event
Yashwanth Nakka
Yashwanth Nakka, PhD Candidate, GALCIT,

Autonomous science-driven orbit (or goal) selection and planning for safety under uncertainty enable efficient and adaptable missions. In the first part of the talk, I present an information-based guidance and control architecture for inspection or mapping a target spacecraft in a low Earth orbit using multiple observer spacecraft. In this architecture, we compute orbits and reconfiguration strategies by maximizing the information gain from distributed observations of a target spacecraft. The resulting motion trajectories jointly consider the observational coverage of the target spacecraft and the fuel/energy cost. I will discuss a mission simulation to visually inspect the target spacecraft and experimental validation of the architecture on Caltech's three-degree-of-freedom robotic spacecraft dynamics simulator testbed.

In the second part of the talk, I will present gPC-SCP: Generalized Polynomial Chaos-based Sequential Convex Programming method to compute a sub-optimal solution for a continuous-time chance-constrained stochastic nonlinear optimal control problem. The approach enables motion planning and control of robotic systems under uncertainty. I will discuss the application of the gPC-SCP method for the following three test cases: 1) collision checking under uncertainty in actuation, 2) collision checking with stochastic obstacles, and 3) safe trajectory tracking under uncertainty in the dynamics and obstacle location by using a receding horizon control approach. I will briefly cover, the experimental validation of the gPC-SCP method on the robotic spacecraft testbed. Extending this method, I will discuss a novel approach for optimal motion planning for safe exploration that integrates the chance-constrained stochastic optimal control with dynamics learning and feedback control. I will conclude the talk with a brief review of the contributions, impact, and possible extensions of the above methods.

Live Zoom Event: <https://caltech.zoom.us/j/84737586094>

Box Recordings for Caltech: <https://caltech.box.com/s/ktk4t67cwdgqp2eky4duoxcahqqmt9hk>

For more information, please contact Benjamin Riviere by email at [email protected].