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Controls, Autonomy and Robotics Seminar

Advances in Autonomous Guidance, Navigation and Control for Miniaturized Distributed Space Systems

Thursday, March 22, 2018
3:30 pm

WRW 113

Two key trends are revolutionizing the way humans conduct spaceflight, namely, the miniaturization of satellites (e.g., micro- and nano-satellites) and the distribution of payload tasks among multiple coordinated units (e.g., formation-flying, on-orbit servicing, fractionation, swarms). The combination of these approaches promises breakthroughs in space science (e.g., imaging of earth-like planets, characterization of gravitational waves), remote sensing (e.g., synthetic aperture radar interferometry, aeronomy, gravimetry), and space exploration (e.g., lifetime extension, assembly of structures, space debris removal).

Irrespective of the specific application, future miniature distributed space missions require a high level of autonomy to maintain and reconfigure the relative motion of the participating vehicles within the prescribed accuracy and range of operations. Especially on small spacecraft, these requirements are hard to meet due to the limited resources, and the chief goal of current research and development is to pave the way for the autonomous Guidance, Navigation, & Control (GN&C) of “self-driving nanosatellites”.

Leveraging the author’s contributions to the most recent satellite formation-flying and rendezvous missions in low earth orbit (TanDEM-X, PRISMA, BIROS), this presentation addresses the astrodynamics and GN&C algorithms under developments to enable a new class of space instruments. A novel low-cost mission concept developed by the author is introduced, the so-called miniaturized Distributed Occulter/Telescope (mDOT). mDOT consists of two small formation-flying satellites precisely positioned in high elliptical orbit to directly image exozodiacal dust and exoplanets. Finally, the high-fidelity hardware-in-the-loop virtual reality and physical testbed under development at Stanford for the verification of the new GN&C algorithms is presented.

Contact  Dr. Maruthi Akella makella@mail.utexas.edu or (512) 471-9493