Papers

18

Total Citations

1,017

H-Index

17

About

David Kriegman is a pioneering researcher in robotics and computer vision, whose work has profoundly shaped how autonomous mobile robots perceive, navigate, and interact with their environments. His early and highly influential research on stereo vision-based navigation — accumulated nearly 300 citations — demonstrated that robots could autonomously operate in complex, previously unknown indoor environments by fusing stereo vision, odometry, and symbolic world modeling. This foundational contribution helped establish the field of vision-based robotic navigation. Kriegman's subsequent work expanded these principles into systematic environment exploration, landmark recognition, and domain-independent navigation, addressing both structured and unstructured settings. His investigations into structure-from-motion in two dimensions offered elegant mathematical solutions for mobile robots constructing environmental maps from visual data. He also made notable contributions to robotic manipulation, including part-feeding algorithms for industrial assembly and the computational architecture of the landmark Utah/MIT dexterous hand. Collectively, his research bridges perception, planning, and control — a synthesis reflected in his co-editorship of *The Confluence of Vision and Control*. With hundreds of citations across a decade of prolific output, Kriegman's legacy represents a cornerstone of modern autonomous robotics, offering students and researchers an invaluable foundation for understanding how machines learn to see and move intelligently.

Research Focus

Key Achievements

17
H-Index
18
Papers
1,017
Total Citations
57
Avg Citations/Paper
🏆 Most Cited Paper
Stereo vision and navigation in buildings for mobile robots
293 citations · 1989
📈 Most Prolific Year: 2002 (7 Papers)
🤝 Key Collaborators: 23
🏛 Institutions: Stanford University, Yale University, Center for Systems Biology, University of Illinois Urbana-Champaign

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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