Meryem El mahri
Papers
1
Total Citations
8
H-Index
1
About
Meryem El Mahri is a robotics researcher whose work focuses on advancing autonomous navigation through improved path planning algorithms. Her primary research areas include mobile robotics, sampling-based motion planning, and optimization of autonomous systems. Her most notable contribution, detailed in her highly cited 2022 paper "A new sampling strategy to improve the performance of mobile robot path planning algorithms," addresses a critical bottleneck in Rapidly-exploring Random Tree (RRT) and RRT* algorithms. By introducing an innovative sampling strategy, she significantly enhances the efficiency and convergence speed of these algorithms in complex, high-dimensional environments—a key challenge for real-world robotic applications. This work has garnered 8 citations, demonstrating its relevance to the field. El Mahri’s research bridges theoretical algorithm design and practical deployment, offering tangible improvements for mobile robots operating in cluttered or dynamic spaces. Her contributions are particularly valuable for researchers and engineers working on autonomous navigation, as they provide a more robust foundation for real-time decision-making in robotics.
Research Focus
Key Achievements
Top Papers
- 1