Celina Haffele

Papers

Total Citations

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About

Celina Haffele’s research lies at the intersection of underwater robotics, autonomous navigation, and neural-inspired environmental mapping. Her most influential work, “Visual Odometry and Mapping for Underwater Autonomous Vehicles” (2010, 10 citations), introduced a pioneering method for real-time visual odometry and mapping using only online visual data—enabling autonomous inspection tasks and remote operator assistance in challenging subsea environments. This contribution addresses a critical gap in underwater robotics, where GPS is unavailable and sensor noise is high. Haffele further advanced robotic perception through her work on self-organizing maps. In “Self-Organizing Mapping of Robotic Environments Based on Neural Networks” (2012, 3 citations), she proposed a neural network-based approach for mapping both structured and unstructured environments, allowing robots to determine free space and establish landmarks for localization. Her follow-up study, “Spatial and Perceptive Mapping Using Semantically Self-Organizing Maps” (2012, 2 citations), integrated multi-sensor data into a consistent, semantically rich map representation—enhancing a robot’s ability to understand and navigate its surroundings. Though her citation counts are modest, Haffele’s work represents foundational steps in combining neural computation with practical robotic mapping, particularly for underwater domains. Her contributions offer valuable insights for researchers developing autonomous systems in GPS-denied or perceptually complex environments.