Luis M. Bergasa
Papers
68
Total Citations
1,348
H-Index
22
About
Luis M. Bergasa is a prominent researcher whose work spans mobile robotics, autonomous vehicles, and assistive technologies — fields where his contributions have significantly advanced both theoretical understanding and real-world application. His research portfolio reveals two defining threads: robust visual localization for long-term autonomous navigation and accessible human-machine interfaces. Bergasa's foundational work in the early 2000s introduced electrooculography (EOG)-based wheelchair control systems, using eye movements and neural networks to empower users with limited mobility — work that attracted over 140 combined citations and demonstrated his commitment to socially impactful engineering. His research then evolved toward autonomous navigation, producing highly cited methods for life-long visual topological localization, including the ABLE-M algorithm and CNN feature fusion techniques for seasonal appearance changes, collectively cited nearly 200 times. His multi-sensorial SLAM systems for GPS-denied micro aerial vehicles further broadened his influence across aerial robotics. More recently, Bergasa has tackled autonomous driving challenges, contributing to HD map exploitation using OpenDRIVE standards and simulation-based training pipelines using the CARLA simulator. His sustained productivity across assistive robotics, computer vision, and autonomous systems makes him an essential figure for researchers working at the intersection of perception, localization, and intelligent mobility.
Research Focus
Key Achievements
Top Papers
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- 5EOG guidance of a wheelchair using neural networks64 citations · 2002
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- 8HD maps: Exploiting OpenDRIVE potential for Path Planning and Map Monitoring38 citations · 2022
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- 10Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes32 citations · 2015