Papers
8
Total Citations
446
H-Index
6
About
Eric Royer is a computer vision and robotics researcher whose work has significantly advanced the field of autonomous mobile robot navigation and localization. His most influential contribution, "Monocular Vision for Mobile Robot Localization and Autonomous Navigation" (2007), has garnered over 324 citations, establishing him as a leading voice in vision-based robotics. This landmark work demonstrated how a single camera could serve as a reliable sensing modality for robot localization in real-world urban environments — a challenge of considerable practical significance. A recurring theme across Royer's research is the calibration of non-overlapping camera systems, where he developed innovative methods enabling multi-camera rigs to be accurately calibrated even when their fields of view do not share common scene features. These contributions, published in 2010 and 2011, have found broad application in mobile robotics platforms. His work on efficient planar feature matching, including GPU-accelerated approaches, reflects a consistent drive to make vision-based localization computationally practical for real-time deployment. Royer's doctoral thesis (2006) laid the theoretical groundwork for much of this research, combining 3D mapping and monocular vision into a coherent framework for autonomous navigation in outdoor environments.
Research Focus
Key Achievements
Top Papers
- 1Monocular Vision for Mobile Robot Localization and Autonomous Navigation324 citations · 2007
- 2Fast calibration of embedded non-overlapping cameras44 citations · 2011
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- 5Efficient planar features matching for robot localization using GPU8 citations · 2010
- 6Matching Planar Features for Robot Localization7 citations · 2009
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- 8Vision-Based Hybrid Map Building for Mobile Robot Navigation3 citations · 2015