Papers
9
Total Citations
1,245
H-Index
6
About
Stephanie Lowry is a leading researcher in robotics and computer vision, whose work has fundamentally advanced the field of visual place recognition. Her primary research areas include long-term robot autonomy, visual localization, and perception in dynamic and challenging environments. Lowry is best known for her seminal survey, "Visual Place Recognition: A Survey" (2015), which has amassed over 1,071 citations and serves as a foundational reference for the community, synthesizing decades of progress on a core problem in mobile robotics. She has made major contributions to developing robust localization systems that operate under extreme appearance and viewpoint changes, introducing innovative methods such as supervised and unsupervised linear learning techniques for place recognition in changing environments. Her work on sequence searching with deep-learnt depth further advanced condition- and viewpoint-invariant route-based recognition. Lowry has also explored bio-inspired multi-scale place recognition and, more recently, applied RGB-D perception to agricultural robotics. Her research consistently tackles the challenge of enabling robots to navigate persistently and reliably in real-world settings, making her a pivotal figure in the quest for truly autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Visual Place Recognition: A Survey1,071 citations · 2015
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- 4Bio-inspired homogeneous multi-scale place recognition23 citations · 2015
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- 8Improving Localisation Accuracy using Submaps in warehouses2 citations · 2018
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