Nicola Bellotto
University of Essex, University of Lincoln, University of Padua
Papers
58
Total Citations
1,586
H-Index
21
About
Nicola Bellotto is a leading researcher in mobile robotics, specializing in human detection and tracking, sensor fusion, and assistive robotics. His work has fundamentally shaped how robots perceive and interact with people in dynamic, real-world environments. Bellotto's 2008 paper on multisensor-based human detection and tracking for mobile service robots — now cited over 300 times — established a cornerstone framework for human-robot interaction, demonstrating how fusing data from multiple sensors enables robust people-tracking in complex settings. Building on this foundation, he pioneered online learning approaches for 3D LiDAR-based human classification, developing adaptive frameworks that allow robots to continuously improve their perception capabilities without manual retraining, work that has collectively accumulated nearly 300 additional citations. His contributions extend into assistive robotics through the ENRICHME project, which deployed socially aware robots to support elderly individuals living independently at home. Bellotto has also explored swarm robotics and qualitative analysis of human-robot spatial behavior, reflecting the breadth of his interests. With over 800 citations across his most influential works, his research has made a lasting impact on making robots safer, smarter, and more socially competent companions.
Research Focus
Key Achievements
Top Papers
- 1Multisensor-Based Human Detection and Tracking for Mobile Service Robots309 citations · 2008
- 2Online learning for human classification in 3D LiDAR-based tracking122 citations · 2017
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- 5Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method75 citations · 2014
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- 7Real-time multisensor people tracking for human-robot spatial interaction62 citations · 2015
- 8Vision and Laser Data Fusion for Tracking People with a Mobile Robot46 citations · 2006
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