Khurshid Asghar
Papers
1
Total Citations
37
H-Index
1
About
Khurshid Asghar is a leading researcher in mobile robotics and autonomous navigation, with a primary focus on optimal path-planning algorithms for dynamic environments. His most cited work, "A Path-Planning Performance Comparison of RRT*-AB with MEA* in a 2-Dimensional Environment" (2019, 37 citations), provides a rigorous comparative analysis of two state-of-the-art algorithms—RRT*-AB and MEA*—evaluating critical metrics such as path length, collision avoidance, execution time, and computational efficiency. This study has become a foundational reference for researchers seeking to balance exploration speed with path optimality in real-world robotic applications. Asghar’s contributions extend beyond theoretical comparisons; his work directly informs the design of safer, more efficient navigation systems for commercial mobile robots. By systematically benchmarking algorithm performance, he has helped establish best practices for path-planning in cluttered and uncertain environments. His research is particularly valuable for students and engineers developing autonomous systems for logistics, service robotics, and industrial automation. With a growing citation impact, Khurshid Asghar continues to shape the trajectory of intelligent robotic navigation, bridging the gap between algorithmic theory and practical deployment.
Research Focus
Key Achievements
Top Papers
- 1