Hamid Nourisola

Papers

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About

Hamid Nourisola’s research centers on autonomous navigation, robust control, and robotic manipulation—fields where precision and adaptability are critical. His most cited work, “3D inertial algorithm of SLAM for using on UAV” (2016, 6 citations), tackles the foundational challenge of simultaneous localization and mapping (SLAM) for unmanned aerial vehicles, proposing an efficient inertial algorithm that enhances autonomous flight in unknown environments. This contribution is complemented by his work on adaptive control, notably “Adaptive H∞ controller based on GA-hybrid wavelet RBF for robot arm” (2014, 2 citations), which fuses genetic algorithms with wavelet neural networks to achieve robust tracking control under uncertainty. More recently, in “Pre-Compensated Proportional Derivative Sliding Mode Controller Design for Image Based Visual Servoing” (2019, 2 citations), Nourisola addresses visual servoing for robot manipulators, integrating sliding mode control with pre-compensation to ensure fast, accurate motion despite system uncertainties. Across these studies, Nourisola demonstrates a consistent commitment to advancing intelligent control and perception for autonomous systems, laying groundwork for more reliable UAV navigation and dexterous robotic manipulation.