Asim Imdad Wagan

National Institute of Standards and Technology

Papers

Total Citations

H-Index

About

Asim Imdad Wagan’s research bridges the critical domains of 3D object recognition and robotic perception, with a focus on enabling machines to interpret and navigate physical environments. His most cited work, “3D Part Identification Based on Local Shape Descriptors” (2008), addresses the growing need for robust 3D object recognition in fields ranging from computer vision and CAD/CAM to robotics and molecular biology. By developing local shape descriptors, Wagan’s approach allows for precise identification of 3D parts, a foundational contribution to automated design and spatial understanding. His subsequent work, “Quantitative Assessment of Robot-Generated Maps” (2009), extends this expertise into mobile robotics, proposing methods to evaluate the accuracy of maps built by autonomous robots—a key challenge for reliable navigation and exploration. Though his citation counts are modest, Wagan’s research tackles fundamental problems in shape analysis and robotic mapping, laying groundwork for later advances in 3D perception and autonomous systems. His interdisciplinary focus on both geometric modeling and robotic mapping highlights a commitment to practical, real-world applications, making his contributions valuable for students and researchers working at the intersection of computer vision, robotics, and computational geometry.