Mohamed Naveed Gul Mohamed

Texas A&M University

Papers

2

Total Citations

5

H-Index

2

About

Mohamed Naveed Gul Mohamed is a robotics and control theorist whose work bridges the gap between fundamental optimal control and practical robotic deployment. His research centers on two key areas: stochastic nonlinear control and precision localization for warehouse robotics. In his 2020 paper "Near Optimality and Tractability in Stochastic Nonlinear Control," Mohamed tackles Bellman's infamous curse of dimensionality, presenting a principle for tractable feedback design that first solves a nominal open-loop problem before applying a suitable correction—a contribution that has earned 2 citations for its theoretical elegance. His most impactful work, "Structure Aided Odometry (SAO)" (2021, 3 citations), introduces a novel analytical odometry technique based on semi-absolute localization, specifically designed for precision-warehouse robotic assistance in environments with low feature variation. This practical innovation addresses a critical challenge in industrial automation, where traditional localization methods fail in repetitive, feature-sparse settings. Mohamed’s dual focus on theoretical tractability and real-world application positions him as a rising figure in robotics and control, with his SAO technique offering a promising solution for the next generation of autonomous warehouse systems.

Research Focus

Key Achievements

2
H-Index
2
Papers
5
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Structure Aided Odometry (SAO) : A Novel Analytical Odometry Technique Based on Semi-Absolute Localization for Precision-Warehouse Robotic Assistance in Environments with Low Feature Variation
3 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Texas A&M University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago