Ahmad Kaleem
Papers
1
Total Citations
3
H-Index
1
About
Ahmad Kaleem’s research centers on autonomous robotic navigation, with a particular focus on developing efficient, planning-based path optimization strategies that reduce reliance on resource-intensive environmental maps. His most-cited work, “Planning-based optimized path for automatic robot navigation” (2018, 3 citations), addresses a core challenge in fully autonomous systems: enabling robots to achieve goals without human intervention while minimizing memory and processing overhead. By proposing laser-based navigation techniques that streamline map usage, Kaleem contributes to making autonomous systems more practical for real-world deployment. Though his citation count is modest, his work tackles foundational problems in robotics—balancing autonomy with computational efficiency—that are critical for advancing fields like service robotics, warehouse automation, and autonomous exploration. His research underscores a commitment to pragmatic solutions that push the boundaries of what robots can accomplish independently, offering valuable insights for students and engineers seeking to build smarter, more self-sufficient robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Planning-based optimized path for automatic robot navigation3 citations · 2018