Alexandra Raibolt
Papers
1
Total Citations
2
H-Index
1
About
Dr. Alexandra Raibolt is a robotics researcher specializing in autonomous navigation and embedded computer vision, with a focus on Simultaneous Localization and Mapping (SLAM) systems. Her work centers on improving Loop Closure Detection (LCD)—a critical step for robots to recognize previously visited locations and correct drift in their maps. In her most-cited paper, "Comparative Evaluation of Feature Descriptors Through Bag of Visual Features with Multilayer Perceptron on Embedded GPU System" (2020), she systematically compared handcrafted feature descriptors against machine learning approaches for LCD, demonstrating how a Multilayer Perceptron combined with Bag of Visual Features can enhance performance on resource-constrained embedded GPU platforms. This work bridges the gap between traditional handcrafted methods and modern deep learning, offering practical solutions for real-time autonomous systems. While her citation count is still growing, her contributions are foundational for researchers developing efficient, robust SLAM pipelines for mobile robots. Dr. Raibolt’s research is particularly valuable for students and engineers working on low-power autonomous systems, where computational efficiency is paramount.
Research Focus
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Top Papers
- 1