Papers
5
Total Citations
950
H-Index
4
About
Jorge Fuentes-Pacheco is a leading researcher in robotics, computer vision, and precision agriculture, with a career spanning foundational work in visual simultaneous localization and mapping (SLAM) to cutting-edge deep learning applications. His most influential contribution is the landmark survey "Visual simultaneous localization and mapping: a survey" (2012), which has amassed over 886 citations, serving as an essential reference for researchers and practitioners in autonomous navigation. Fuentes-Pacheco has also made significant strides in agricultural robotics, notably through his work on "Fig Plant Segmentation from Aerial Images Using a Deep Convolutional Encoder-Decoder Network" (2019, 42 citations), where he developed novel solutions for crop segmentation using aerial robots—a critical task in precision agriculture. Earlier in his career, he advanced robotic manipulation with his research on binocular visual tracking and grasping of moving objects, incorporating 3D trajectory predictors to enable real-time, robust grasping even under occlusion. His more recent work on binary pattern descriptors for scene classification further demonstrates his versatility, contributing to automatic surveillance and robotic navigation. Fuentes-Pacheco’s research consistently bridges theoretical innovation with practical, real-world applications, making him a key figure in the evolution of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Visual simultaneous localization and mapping: a survey886 citations · 2012
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- 4
- 5Binary Pattern Descriptors for Scene Classification2 citations · 2020