Papers
3
Total Citations
27
H-Index
3
About
Wahid Nouibat’s research centers on robotics, autonomous navigation, and intelligent control systems, with a particular focus on unmanned aerial vehicles (UAVs) and humanoid robots. His most influential work, “Evolutionary Autopilot Design Approach for UAV Quadrotor by Using GA” (2019, 19 citations), introduces a genetic algorithm-based method for optimizing quadrotor autopilots, offering a novel evolutionary approach to flight stability and control. This contribution is notable for its potential to enhance autonomous UAV performance in dynamic environments. Nouibat has also made strides in humanoid robotics, as seen in his 2013 paper on kinematic modeling of an 18-degree-of-freedom humanoid robot (4 citations), where he developed a new modeling approach for the HR-ARP prototype, advancing direct and inverse kinematics. Additionally, his work on fuzzy reactive navigation for mobile robots (2013, 4 citations) proposes an offline adaptive neuro-fuzzy system that enables obstacle avoidance and target reaching, blending fuzzy logic with neural adaptation. Though his citation counts are modest, Nouibat’s research demonstrates a commitment to integrating evolutionary algorithms and fuzzy systems into practical robotic applications, laying groundwork for future innovations in autonomous navigation and control.
Research Focus
Key Achievements
Top Papers
- 1Evolutionary Autopilot Design Approach for UAV Quadrotor by Using GA19 citations · 2019
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