Mohamed Njah
Papers
8
Total Citations
30
H-Index
3
About
Mohamed Njah is a robotics researcher whose work centers on intelligent motion planning and trajectory optimization for mobile robots operating in complex, dynamic environments. His primary research focus is the development of novel, nature-inspired algorithms that combine Particle Swarm Optimization (PSO) with force field methods to enable safe and efficient robot navigation. Njah’s major contributions include the creation of several innovative approaches, such as PSO-CF² (Canonical Force Field) and PSO-DVSF² (Dynamic Variable Speed Force Field), which allow robots to plan optimal paths while avoiding collisions with both fixed and moving obstacles. His most-cited paper, “PSO optimized F2 based mobile robot motion planning approaches for fixed and mobile targets” (2022), has garnered 6 citations, alongside his earlier foundational works from 2015 that introduced the core PSO-CF² and PSO-DVSF² methods. Njah has also explored comparative studies, such as “Which is Better for Mobile Robot Trajectory Optimization: PSO or GA?” (2020), and extended his algorithms to track moving targets in unknown environments. With a cumulative citation count exceeding 30 across his top papers, Njah’s work has provided a robust framework for autonomous robot navigation, offering practical solutions for real-world applications in manufacturing, logistics, and service robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2PSO-CF2: A new method for the path planning of a mobile robot6 citations · 2015
- 3PSO-DVSF2: A new method for the path planning of mobile robots5 citations · 2015
- 4
- 5
- 6
- 7Which is Better for Mobile Robot Trajectory Optimization: PSO or GA?2 citations · 2020
- 8PSO optimization of mobile robot trajectories in unknown environments2 citations · 2016