AEM Colloquium Series: Professor Ran Dai

Smart Decision-Making for Autonomous Systems in Space Exploration Missions

Many autonomous systems benefit from efficient operations and advanced autonomy levels in ambitious space missions, from human exploration of Mars to on-orbit servicing, assembly, and manufacturing (OSAM) missions. However, complex system dynamics, changing operating environments, and stringent mission constraints make reliable, resource-efficient operations challenging. With limited human intervention, real-time decision-making that connects motion planning with task-level reasoning plays a critical role in assuring the reliability and performance of such a system toward mission success.

This talk will present our research on dynamic modeling, scalable optimization, and machine learning based optimal control methods that collectively contribute to advanced decision-making strategies for efficient autonomous systems in space exploration missions. The discussion will highlight applications in two distinct types of autonomous systems. This first concerns space vehicles in complex missions involving multiphase or hybrid operations where onboard propellant is limited and timely ground support is unavailable. The second focuses on origami-inspired deployable systems for OSAM, where systems automatically adapt their shape/functionality to mission needs. These applications share a central challenge: translating complex dynamics and mission requirements into decisions that can be computed and implemented in real time. The talk will highlight how advances in modeling, optimization, and learning are leveraged to support both precise spacecraft motion and adaptable robotic configurations. The overarching goal is to enable autonomous space systems to accomplish increasingly complex missions while making effective use of limited onboard resources.

Dr. Ran Dai is a professor in the School of Aeronautics and Astronautics at Purdue University. Before joining Purdue, she was the Netjets Assistant Professor at The Ohio State University. She received her B.S. degree in Automation Science from Beihang University and her M.S. and Ph.D. degrees in Aerospace Engineering from Auburn University. After graduation, she worked as an engineer in an automotive technology company, Dynamic Research, Inc., and then joined the University of Washington as a postdoctoral fellow. Dr. Dai’s research focuses on control of autonomous systems, numerical optimization, networked dynamical systems, and space robotics. She is an associate fellow of AIAA and a recipient of the NSF Career Award and NASA Early Faculty Career Award. Dr. Dai is serving as an associate editor of the Journal of Guidance, Navigation, and Control and IEEE Transactions on Aerospace and Electronic Systems.