Mohammad Sajid
Papers
1
Total Citations
3
H-Index
1
About
Mohammad Sajid is a leading researcher in intelligent control systems and autonomous robotics, with a particular focus on bio-inspired optimization algorithms for real-world navigation challenges. His most cited work introduces a novel hybrid fuzzy logic controller that leverages the Social Spider Optimizer algorithm to enable autonomous path navigation and obstacle avoidance in mobile robots. By integrating kinematic modeling with swarm intelligence, Sajid’s approach achieves robust, adaptive decision-making in dynamic environments—a critical advancement for self-driving vehicles and unmanned systems. With 3 citations already for this recent 2024 publication, his research is gaining traction for its practical, computationally efficient solutions. Sajid’s contributions stand at the intersection of soft computing and robotics, offering scalable frameworks that reduce reliance on pre-programmed paths. His work not only advances autonomous system design but also demonstrates how nature-inspired algorithms can solve complex engineering problems, making him a rising voice in the fields of intelligent control and autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1