Enabling a New Age in Spaceflight and Space Exploration Through Space Traffic Management and Autonomous Space Systems

Description

Space flight is entering a period of renaissance, with considerable change in the perception of what humanity’s role in space will be. Recently, SpaceX and OneWeb have proposed mega satellite constellations of up to 4,425 satellites in Low Earth Orbit (LEO), which will more than double the number of satellites in LEO. These constellations could revolutionize the telecommunication industry by providing complete global internet coverage. The economic gains of completely connecting rural areas and developing nations cannot be understated, however, the current space infrastructure is not capable of handling such a dramatic increase in the number of active satellites. Therefore, there is a critical need for new solutions to the problem of Space Traffic Management (STM) and Space Situational Awareness (SSA).

Conversely, the technologies that are revolutionizing near-Earth spaceflight will provide new opportunities for deep space exploration. Future science-driven interplanetary missions and/or missions to Lagrangian points and asteroids will require advanced guidance and navigation algorithms that are able to adapt to more demanding mission requirements. For example, future missions to asteroids and comets will require that the spacecraft be able to autonomously navigate in uncertain dynamical environments by executing a precise sequence of maneuvers (e.g. hovering, landing, touch-and-go) based on information collected during the close-proximity operations. These missions will require approaches for landing at selected locations with pinpoint accuracy while autonomously flying fuel-efficient trajectories.

This presentation will discuss new methods for enabling STM and autonomous space systems. In particular, this presentation will discuss a new method for assessment of confidence in position knowledge through improved satellite drag modeling, which is critical for STM. This presentation will also discuss novel methods for accurate upper atmospheric density estimation and uncertainty quantification. Furthermore, swarming satellite and robotic systems can offer new ways of exploring our solar system. Current research with the Jet Propulsion Laboratory on swarming systems will also be discussed. Finally, this presentation will provide a vision for the basic research that is needed to enable the future of spaceflight and space exploration.

Professor Linares's research interests are nonlinear estimation, Bayesian inference, uncertainty quantification, optimal control, and reinforcement learning. Dr. Linares joined the faculty of University of Minnesota's Department of Aerospace Engineering and Mechanics as an Assistant Professor in August 2015 after a short tenure as a Postdoctoral Associate at the US Naval Observatory. Prior to moving to Washington D.C., he held a Director's Postdoctoral Fellow position at Los Alamos National Laboratory. Dr. Linares is a recipient of an AFOSR Young Investigator Research Award in 2018.