Shengpeng Guo

National University of Defense Technology

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About

Shengpeng Guo is a leading researcher in the dynamics and control of free-floating space robotic systems, with a focus on on-orbit servicing and autonomous manipulation. His work addresses the fundamental challenge of controlling space robots that are not attached to a fixed base, where any manipulator motion can disturb the spacecraft’s attitude. In his highly cited 2014 paper, "Task space control of free-floating space robots using constrained adaptive RBF-NTSM" (21 citations), Guo introduced a novel adaptive control framework combining radial basis function neural networks with non-singular terminal sliding mode techniques. This approach enables precise task-space tracking while respecting actuator constraints and system uncertainties. His related work on "Reactionless robust finite-time control for manipulation of passive objects by free-floating space robots" (6 citations) developed a method to manipulate passive objects without inducing base disturbances—a critical capability for satellite servicing and debris removal missions. Guo’s contributions are significant for advancing the autonomy and safety of future space operations, providing theoretical foundations for reactionless manipulation and robust finite-time convergence. His research continues to influence the design of control systems for next-generation space robots operating in unconstrained environments.