Interstellar objects are among the last unexplored classes of solar system objects, holding tantalizing information about primitive materials from exoplanetary star systems. They pass through our solar system only once in their lifetime at speeds of tens of kilometers per second, making them elusive.
Hiroyasu Tsukamoto, a faculty member in the Department of Aerospace Engineering in the Grainger College of Engineering, University of Illinois Urbana-Champaign, has developed Neural-Rendezvous—a deep-learning-driven guidance and control framework to autonomously encounter these extremely fast-moving objects.
The research is published in the Journal of Guidance, Control, and Dynamics and on the arXiv preprint server.