Papers
27
Total Citations
520
H-Index
12
About
Alireza Mohammad Shahri is a prominent robotics and control systems researcher whose work has made significant contributions to the fields of mobile robot control, autonomous navigation, and unmanned aerial vehicles. His research is primarily focused on designing advanced adaptive and robust control strategies for nonholonomic robotic systems operating under real-world uncertainties — a notoriously challenging problem in autonomous robotics. Shahri's most influential contributions address trajectory tracking control for wheeled mobile robots, with his 2010 papers on adaptive trajectory tracking and feedback linearizing control accumulating nearly 185 combined citations. These works introduced sophisticated nonlinear control frameworks capable of handling both parametric and nonparametric uncertainties in robot dynamics and actuator behavior. His 2012 study on output feedback tracking without velocity measurement further extended these methods to more practical, sensor-limited scenarios. Beyond ground robots, Shahri has explored quadrotor UAV control through decentralized adaptive and fuzzy adaptive approaches, reflecting the breadth of his expertise. His contributions to autonomous navigation are equally notable, with research on Kalman filter-based SLAM algorithms and mobile robot localization that has shaped estimation techniques for self-navigating systems. Collectively, his body of work — exceeding 440 citations — represents a substantial and enduring impact on intelligent robotic systems research.
Research Focus
Key Achievements
Top Papers
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- 5A novel efficient algorithm for mobile robot localization39 citations · 2013
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- 9Modelling and decentralized adaptive tracking control of a quadrotor UAV16 citations · 2013
- 10A new fuzzy adaptive control for a Quadrotor flying robot15 citations · 2013