Papers

7

Total Citations

28

H-Index

3

About

Xiaoteng Tang is a robotics researcher specializing in the dynamics, control, and motion planning of free-floating space robotic systems. Their work focuses primarily on dual-arm space manipulators operating in microgravity environments — a technically demanding domain where the absence of a fixed base creates complex, coupled dynamic behavior that conventional control strategies struggle to address. Tang's most significant contributions center on developing advanced control methodologies for these challenging systems. Their backstepping robust control framework, the most cited work in their portfolio, employs Lyapunov-based design to guarantee stability in the presence of system uncertainties — a critical requirement for real-world space applications. Complementing this, Tang has investigated radial basis function neural network (RBF-NN) compensation for inertial space tracking, enabling adaptive performance under model inaccuracies. A recurring theme across their research is the nonholonomic nature of free-floating systems; Tang has addressed this through both optimal motion planning formulations and genetic algorithm-based approaches, leveraging momentum conservation principles to derive tractable control designs. With a body of work accumulating over 28 citations, Tang's research provides foundational tools for engineers designing autonomous space manipulation systems — work increasingly relevant as on-orbit servicing and satellite maintenance missions move toward practical deployment.

Research Focus

Key Achievements

3
H-Index
7
Papers
28
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
A backstepping robust control method for free-floating space robot system with dual-arms
9 citations · 2011
📈 Most Prolific Year: 2011 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Minjiang University, Fuzhou University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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