Xiaoli Bai

Rutgers, The State University of New Jersey, Texas A&M University, Mitchell Institute

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About

Xiaoli Bai is a leading researcher in space robotics, whose work bridges the critical gap between theoretical dynamics and real-world orbital operations. Her primary research areas include trajectory planning for free-floating space-robotic systems, satellite pose estimation, and the development of novel mobile robotic platforms for motion emulation. Her most impactful contribution is a pioneering 2017 paper (72 citations) that introduced a convex optimization framework for task-constrained trajectory planning of kinematically redundant, free-floating space robots—a fundamental solution for missions where the base spacecraft is unactuated. More recently, Bai has pushed the boundaries of perception in harsh space environments with her 2025 work on "EvSat3D," which leverages event cameras for robust satellite pose estimation and 3D reconstruction, directly addressing the limitations of traditional frame-based cameras in high-contrast, low-latency orbital scenarios. Her earlier foundational research (2007–2008) on modeling and controlling a mobile robotic system capable of emulating six-degree-of-freedom relative spacecraft motion laid the groundwork for ground-based testing of proximity operations. Through this blend of algorithmic innovation and practical hardware development, Bai is shaping the future of autonomous in-orbit servicing and debris removal.