Maurilio Di Cicco
Papers
6
Total Citations
218
H-Index
4
About
Maurilio Di Cicco is a robotics researcher whose work spans agricultural automation, cultural heritage preservation, and autonomous system calibration. His primary research areas include precision agriculture robotics, 3D sensing, and autonomous exploration. Di Cicco's most impactful contribution is his 2017 work on automatic model-based dataset generation for crop and weed detection (172 citations), which addressed the critical challenge of selective weeding in agricultural robotics by enabling fast and accurate plant classification. This work has significant implications for reducing herbicide use and improving farming efficiency. He also developed a non-parametric calibration method for depth sensors (19 citations) and an unsupervised approach for calibrating wheeled mobile platforms (10 citations), allowing robots to autonomously refine their kinematic parameters. Di Cicco contributed to the ROVINA project, exploring and mapping challenging environments like catacombs (12 citations), demonstrating his expertise in deploying robots for digital preservation of archaeological sites. His work on mapping infected crops through UAV inspection further showcases his versatility in applying robotics to real-world problems. Di Cicco's research exemplifies how robotics can address diverse challenges from agriculture to cultural heritage.
Research Focus
Key Achievements
Top Papers
- 1
- 2Non-parametric calibration for depth sensors19 citations · 2015
- 3Exploration and mapping of catacombs with mobile robots12 citations · 2013
- 4Unsupervised calibration of wheeled mobile platforms10 citations · 2016
- 5
- 6