Edmundo Guerra
Papers
13
Total Citations
178
H-Index
7
About
Edmundo Guerra is a leading researcher in robotics and autonomous systems, with a primary focus on precision agriculture, simultaneous localization and mapping (SLAM), and multi-sensor fusion for unmanned aerial vehicles (UAVs). His most impactful contribution is a robust method for detecting and estimating the depth of table grapes and their peduncles for robot harvesting, combining monocular depth estimation with convolutional neural networks—a work that has garnered 52 citations and directly advances agricultural automation. Guerra has also made significant strides in monocular visual SLAM, notably developing a cooperative UAV–target system (27 citations) and enhancing feature initialization for autonomous robots (21 citations). His research extends to industrial applications, where he has fused UAV visual and laser sensors for pipe detection and positioning (19 citations), and to environmental monitoring, with a virtual sensor network for smart wastewater monitoring (18 citations). Guerra’s work on multi-UAV SLAM configurations and human-robot collaborative mapping further underscores his expertise in cooperative autonomy. With a career spanning over a decade, his innovations are pivotal for real-world deployment of autonomous robots in agriculture, industry, and infrastructure inspection.
Research Focus
Key Achievements
Top Papers
- 1
- 2Monocular Visual SLAM Based on a Cooperative UAV–Target System27 citations · 2020
- 3Monocular SLAM for Autonomous Robots with Enhanced Features Initialization21 citations · 2014
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- 8A solution for robotized sampling in wastewater plants7 citations · 2016
- 9Human-robot SLAM in industrial environments4 citations · 2015
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