Papers
22
Total Citations
190
H-Index
8
About
Abdollah Homaifar is a leading figure in robotics and intelligent control systems, with pioneering contributions spanning autonomous navigation, motion planning, and teleoperation. His work is distinguished by the innovative fusion of evolutionary algorithms, fuzzy logic, and artificial potential fields to solve complex, real-world robotic challenges. Notably, his 2020 paper on a stable analytical solution for car-like robot trajectory tracking (39 citations) provides a mathematically rigorous method guaranteeing global exponential stability, a significant advance for autonomous vehicle control. Earlier foundational work, such as his 2002 study linking artificial potential fields to constrained optimization (17 citations), introduced a simple genetic hill-climbing algorithm that remains influential in robot navigation. Homaifar has also made impactful contributions to teleoperation under time-varying delays (19 citations), hybrid fuzzy-PID controller design (13 citations), and multi-UAV system performance evaluation. His research consistently bridges theoretical optimization with practical implementation, addressing critical issues like singularity avoidance and real-time reactive behavior. With a career spanning over two decades, Homaifar’s work is essential reading for students and researchers in robotics, control systems, and artificial intelligence, offering both foundational insights and cutting-edge solutions for autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 4Soft computing-based design and control for mobile robot path tracking13 citations · 2003
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- 7A symbolic motion planning approach for the reach-avoid problem9 citations · 2016
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- 9Hybrid evolutionary motion planning via visibility-based repair8 citations · 2002
- 10Reactive real time behavior for mobile robots in unknown environments6 citations · 2004