Mohammad Mansouri

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About

Mohammad Mansouri is a researcher specializing in mobile robotics, with a focus on intelligent control systems and path planning algorithms. His work primarily addresses the challenges of autonomous navigation for nonholonomic mobile robots, combining fuzzy logic, neural networks, and evolutionary computation. In his most cited work, "Tracking control of mobile robot using ANFIS" (2011, 42 citations), Mansouri introduced a novel cascade control architecture using an Adaptive Neuro-Fuzzy Inference System to handle nonlinear trajectory tracking, incorporating future path curvature to improve precision. This contribution has been influential in the development of adaptive controllers for wheeled robots. Earlier, Mansouri pioneered the use of integer genetic algorithms for mobile robot path planning in grid-based environments. His 2008 papers (12 and 6 citations) proposed a compact chromosome representation that significantly reduced computational complexity compared to conventional genetic algorithms, and he introduced a novel repair function to ensure feasible paths. By also considering terrain conditions, Mansouri advanced the practical applicability of evolutionary path planning. His work bridges theoretical control methods with real-world robotic navigation, offering efficient solutions for autonomous systems in constrained environments.