Papers

2

Total Citations

5

H-Index

2

About

M. Ya. Alwardat is a robotics researcher focused on the kinematics, control, and trajectory planning of robotic manipulators. Their primary contributions lie in singularity analysis and avoidance—critical challenges that can compromise a robot’s stability and precision. In their most cited work (2025, 3 citations), Alwardat developed a MATLAB-based method to analyze singular configurations in a six-degree-of-freedom manipulator with a prismatic joint, ensuring controllability and preventing erratic behavior during motion. Building on this, their second key paper (2025, 2 citations) investigates intelligent control methods—such as optimization algorithms and adaptive strategies—to plan trajectories that actively avoid singularities, thereby enhancing operational efficiency and manipulability. Though early in their career, Alwardat’s work addresses a fundamental bottleneck in robotic performance, offering practical simulation-validated solutions that bridge theoretical kinematics with real-world control. Their research is particularly valuable for students and engineers working on industrial manipulators, collaborative robots, or autonomous systems where smooth, singularity-free motion is essential. With a clear focus on computational tools and intelligent control, Alwardat is establishing a promising trajectory in robotics and automation research.

Research Focus

Key Achievements

2
H-Index
2
Papers
5
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Singularity analysis of a robotic manipulator with six degrees of freedom using MatLab
3 citations · 2025
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Peter the Great St. Petersburg Polytechnic University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago