Papers
32
Total Citations
412
H-Index
12
About
M. J. Mahjoob is a robotics and control systems researcher whose work has made significant contributions to mobile robot motion planning, control, and dynamics. His research is particularly focused on spherical robots — a challenging class of non-holonomic systems — with landmark studies addressing mathematical modelling, stabilization, and motion control on inclined and variable-slope planes. His 2016 paper on pendulum-driven spherical robots using Lagrangian formulation and PID control has garnered 43 citations, while his dynamic programming-based optimal motion planning approach accumulated 40 citations, together establishing him as a leading voice in spherical robot mechanics. Beyond spherical robotics, Mahjoob has explored bio-inspired path planning, introducing a bee colony algorithm for real-time mobile robot navigation that attracted 36 citations. His portfolio further spans reinforcement learning-based motion planning using XCS classifiers, terminal sliding mode control, adaptive tracking via model-reference systems, and bipedal running gait stabilization through Poincaré map control. His consistent attention to both simulation and experimental validation strengthens the practical relevance of his theoretical contributions. With over 250 cumulative citations across his key publications, Mahjoob's body of work represents a robust and multidisciplinary contribution to intelligent robotics and autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 3Bee colony algorithm for real-time optimal path planning of mobile robots36 citations · 2009
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- 8A control synthesis for reducing lateral oscillations of a spherical robot17 citations · 2011
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- 10Stable active running of a planar biped robot using Poincare map control13 citations · 2013