Sarah Manzoor

Papers

Total Citations

126

H-Index

About

Dr. Sarah Manzoor is a pioneering roboticist whose work bridges the gap between industrial-grade automation and accessible educational platforms. Her primary research focuses on autonomous manipulation, image-guided robotic systems, and open-source hardware for STEM education. Her most influential contribution, "An open-source multi-DOF articulated robotic educational platform for autonomous object manipulation" (2013), has garnered 80 citations and democratized advanced robotics learning by providing a fully documented, affordable platform for students and researchers. Building on this, her 2012 study on an autonomous image-guided robotic system (46 citations) demonstrated a high-precision 5-revolute-joint serial manipulator with 6 degrees of freedom, achieving ±0.5mm positional accuracy at 100mm/s. This work showcased how computer vision can guide real-time industrial-like pick-and-place operations, setting a benchmark for low-cost, high-accuracy robotic systems. Dr. Manzoor’s achievements include developing the first fully open-source educational manipulator capable of autonomous object manipulation, significantly lowering the barrier to entry for robotics research. Her work has been instrumental in advancing both pedagogical tools and practical automation solutions, inspiring a new generation of engineers to explore multi-DOF systems and vision-guided control.