Ali Hasan
Papers
6
Total Citations
53
H-Index
4
About
Ali Hasan is a robotics and mechanical engineering researcher whose work sits at the intersection of autonomous navigation, swarm intelligence, and structural mechanism analysis. Over more than a decade of contributions, he has established himself as a specialist in robot path planning within dynamic environments, consistently developing novel hybrid algorithms that combine classical planning methods — most notably the D* algorithm — with nature-inspired optimization techniques such as Particle Swarm Optimization (PSO), Ant Colony Optimization, and Glowworm Swarm Optimization. His 2017 paper proposing PSO and D*-based planning approaches remains his most influential work, accumulating 22 citations, while his 2018 study on multi-robot coordination using Max–Min Ant Colony Optimization added a meaningful dimension by addressing competitive and centralized multi-agent scenarios. Beyond robotics navigation, Hasan has also contributed to kinematic chain analysis, with an early 2011 paper on isomorphism detection in mechanisms and robot manipulators earning 8 citations. Collectively, his research addresses fundamental challenges in making robots safer, more efficient, and more adaptable — work of growing relevance as autonomous systems become increasingly embedded in modern industrial and real-world environments.
Research Focus
Key Achievements
Top Papers
- 1Robot path planning based on PSO and D* algorithmsin dynamic environment22 citations · 2017
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