M. Roozegar
Papers
8
Total Citations
191
H-Index
7
About
M. Roozegar is a leading researcher in the field of nonholonomic spherical robotics, with a primary focus on the modelling, control, and motion planning of pendulum-driven spherical robots (PDSRs). His work addresses the fundamental challenges of stabilizing and guiding these unique, highly mobile robots across complex terrains, including inclined and variable-slope planes. Roozegar’s major contributions span both theoretical development and experimental validation. He has pioneered the use of Lagrangian formulations for dynamic modelling and has applied a diverse suite of advanced control strategies, including PID, terminal sliding mode, and model-reference adaptive control, to achieve robust trajectory tracking. His work on optimal motion planning using dynamic programming and reinforcement learning (XCS-based algorithms) has been particularly influential, with his 2016 paper on modelling and control of a PDSR on an inclined plane accumulating 43 citations, and his 2016 paper on optimal motion planning reaching 40 citations. By integrating adaptive estimation techniques, such as fuzzy-based speed gradient algorithms, Roozegar has also advanced the field’s ability to handle parametric uncertainties in nonlinear, chaotic robotic systems. His research is essential reading for anyone working on non-conventional mobile robots for hazardous environments.
Research Focus
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Top Papers
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- 8Motion planning of a spherical robot using eXtended Classifier Systems5 citations · 2013