Michael J. Seelinger

University of Notre Dame, Urbana University

Papers

10

Total Citations

174

H-Index

6

About

Michael J. Seelinger is a robotics researcher whose career has centered on vision-guided robotic systems, with particular expertise in camera-space manipulation, uncalibrated visual control, and autonomous industrial applications. His most influential contribution — "Automatic Visual Guidance of a Forklift Engaging a Pallet" (2006, 75 citations) — demonstrated the practical power of computer vision in automating material handling, a problem with significant real-world industrial relevance. Building on this, his 2003 work on multi-camera, multi-target robot control (30 citations) established efficient frameworks for three-dimensional robotic guidance without relying on camera calibration, a technically demanding and impactful advance. Seelinger's earlier research laid critical groundwork in applying uncalibrated vision to robotic plasma spraying (1998, 27 citations), showing that vision-based systems could achieve high precision in both position and orientation for complex coating operations. His 1999 paper on camera-space target disposition further refined estimation methods for manipulator control in unstructured environments. Across his body of work, Seelinger consistently pursued practical, calibration-free solutions to difficult robotic guidance problems, spanning industrial manipulators, construction robots, and heterogeneous mobile systems — reflecting a career dedicated to bridging theoretical vision-based control with real-world automation challenges.

Research Focus

Key Achievements

6
H-Index
10
Papers
174
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
Automatic visual guidance of a forklift engaging a pallet
75 citations · 2006
📈 Most Prolific Year: 2006 (2 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University of Notre Dame, Urbana University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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