Amir Khan
Papers
2
Total Citations
5
H-Index
2
About
Amir Khan’s research focuses on making agricultural robotics accessible and practical for low-income farming communities, particularly in South Asia. His core contributions lie in developing simplified, vision-based navigation systems for autonomous wheat harvesting—a domain where cost and complexity have historically limited adoption. Khan’s most cited work, “Simplified vision based automatic navigation for wheat harvesting in low income economies” (2015, 3 citations), directly addresses the extreme weather and resource constraints faced by smallholder farmers, proposing scalable methodologies that replace expensive sensors with affordable computer vision. His follow-up paper, “Low Cost Semi-Autonomous Agricultural Robots In Pakistan” (2015, 2 citations), further refines this approach by emphasizing human-robot collaboration, aiming to complement rather than replace manual labor. Though his citation counts are modest, Khan’s work is notable for its targeted impact on a pressing global challenge: bridging the automation gap in regions where traditional agricultural robotics remain out of reach. His research stands as a pragmatic, equity-driven contribution to the field of agricultural robotics, offering a blueprint for low-cost automation that prioritizes accessibility over complexity.
Research Focus
Key Achievements
Top Papers
- 1
- 2