Ali Hassani

K.N.Toosi University of Technology

Papers

5

Total Citations

51

H-Index

4

About

Ali Hassani is a robotics researcher specializing in the control and dynamics of parallel manipulators, with a particular focus on translational and spherical parallel robots, as well as haptic systems for surgical training. His work addresses critical challenges in model-based control, including kinematic and dynamic uncertainties, bounded input constraints, and practical adaptive regulation. Hassani’s most cited paper (2023, 30 citations) introduces an adaptive position feedback controller for parallel robots that handles both kinematic and dynamic uncertainties, a significant contribution for large-scale or deployable manipulators interacting with their environment. He has also developed full dynamic models for 3-UPU translational parallel manipulators and spherical parallel robots, providing essential formulations for model-based control schemes. Notably, his research on the dynamic calibration and trajectory control of ARASH:ASiST—a 3-DOF haptic device for intraocular surgery training—demonstrates the applied impact of his work in medical robotics. With a growing citation record and a focus on practical, uncertainty-robust control, Hassani is advancing the reliability and precision of parallel robots in real-world applications.

Research Focus

Key Achievements

4
H-Index
5
Papers
51
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Adaptive Position Feedback Control of Parallel Robots in the Presence of Kinematics and Dynamics Uncertainties
30 citations · 2023
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: K.N.Toosi University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago