Papers
10
Total Citations
86
H-Index
7
About
Roshan Sah is an emerging researcher specializing in space robotics, active debris removal, and autonomous control systems for on-orbit operations. His work addresses one of the most pressing challenges in modern space sustainability: the growing threat of space debris in low Earth orbit (LEO) and the development of intelligent robotic systems capable of mitigating it. Sah's most significant contributions lie in advancing control methodologies for floating space robots — autonomous systems equipped with robotic manipulators mounted on free-floating satellites. His research spans nonlinear Model Predictive Control (MPC), deep reinforcement learning, and hybrid model-dependent learning approaches, offering both classical and AI-driven solutions to the inherently complex dynamics of space-based manipulation. His comparative study of free-floating and rotation-floating control architectures has become a foundational reference in the field, alongside his hardware-in-the-loop validation work that bridges theoretical control design with real-world implementation. With publications spanning satellite chaser design, rendezvous maneuver optimization, and neural field-integrated whole-body control, Sah has accumulated over 85 citations since 2022 — a remarkable output for an early-career researcher. His interdisciplinary approach, combining aerospace engineering, machine learning, and robotics, positions him as a rising voice in the global effort toward sustainable space operations and next-generation on-orbit servicing technologies.
Research Focus
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Top Papers
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- 7The Post Mission Disposal Analysis of PSLV Debris at De-Orbited Altitude9 citations · 2023
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