Alexander Carballo
University of Tsukuba, Nagoya University, Institute for Future Engineering, Gifu University
Papers
20
Total Citations
414
H-Index
10
About
Alexander Carballo is a robotics researcher whose work sits at the intersection of autonomous navigation, sensor fusion, and human-aware mobile robotics. Over more than a decade of sustained research, he has made significant contributions to enabling robots to operate safely and reliably in unstructured, real-world environments populated by people. Carballo's early and most influential work focused on autonomous outdoor robot navigation, exemplified by his team's participation in Japan's Tsukuba Challenge — a demanding 1km autonomous navigation event through busy pedestrian walkways. His 2009 paper on navigation in cluttered outdoor environments has accumulated 90 citations, reflecting its foundational impact on the field. Complementing this, he pioneered multi-layered Laser Range Finder (LRF) fusion techniques for robust people detection, with several papers collectively drawing over 100 citations and establishing him as a key figure in human-robot coexistence research. More recently, Carballo expanded into deep learning-based approaches, contributing a highly cited recurrent neural network method for 3D LiDAR point cloud compression (84 citations), addressing critical data transmission challenges in autonomous driving. His 2018 dataset paper further supports the broader research community studying pedestrian behavior. Across his career, Carballo's work reflects a consistent commitment to practical, deployable autonomous systems in genuinely challenging human environments.
Research Focus
Key Achievements
Top Papers
- 1Autonomous robot navigation in outdoor cluttered pedestrian walkways90 citations · 2009
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