Muhammad Syahmi Ahmad
Papers
1
Total Citations
11
H-Index
1
About
Muhammad Syahmi Ahmad is a robotics researcher specializing in autonomous navigation and human-robot interaction, with a particular focus on assistive technologies for visually impaired individuals. His most-cited work, "Obstacle avoidance for a robotic navigation aid using Fuzzy Logic Controller-Optimal Reciprocal Collision Avoidance (FLC-ORCA)" (2023, 11 citations), introduces a novel hybrid framework that combines fuzzy logic decision-making with optimal reciprocal collision avoidance algorithms. This contribution addresses a critical challenge in robotic guidance systems: enabling safe, adaptive navigation in dynamic environments while maintaining user comfort. By integrating fuzzy logic’s ability to handle uncertainty with ORCA’s collision-free path planning, Ahmad’s approach significantly improves the reliability of robotic navigation aids. His work has implications for both rehabilitation robotics and autonomous systems in crowded spaces. Though early in his career, Ahmad’s research demonstrates a clear trajectory toward creating intelligent, human-centric robotic solutions. His citation record, while modest, reflects growing interest in practical, real-world applications of fuzzy control and collision avoidance, positioning him as an emerging voice in the intersection of assistive robotics and intelligent control systems.
Research Focus
Key Achievements
Top Papers
- 1