Salvatore Troisi
Papers
7
Total Citations
109
H-Index
6
About
Salvatore Troisi is a leading researcher at the intersection of marine robotics, underwater archaeology, and sensor fusion. His work centers on developing innovative robotic platforms and algorithms to explore and reconstruct submerged landscapes, with a particular focus on the culturally rich, volcanic Campi Flegrei region in Italy. Troisi’s major contributions include pioneering the integration of geophysical and photogrammetric sensors on Unmanned Surface Vehicles (USVs) for high-resolution, multi-scale mapping of underwater heritage sites—a methodology showcased in his highly cited 2018 paper on the Nisida Roman harbour (48 citations). Beyond archaeology, he has advanced maritime safety and robotic navigation. His research on low-cost human motion capture for postural stability analysis aboard ships (13 citations) addresses critical ergonomic challenges in the maritime industry. More recently, Troisi has been at the forefront of using deep learning, notably through his DANAE series of papers, to denoise attitude estimation for underwater robots, significantly improving their positioning accuracy in challenging environments. With over 100 total citations, Troisi’s work seamlessly blends hardware innovation with computational intelligence, making him a key figure in both marine robotics and cultural heritage preservation.
Research Focus
Key Achievements
Top Papers
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- 3Low-cost human motion capture system for postural analysis onboard ships13 citations · 2011
- 4DANAE++: A Smart Approach for Denoising Underwater Attitude Estimation10 citations · 2021
- 5DOES: A Deep Learning-Based Approach to Estimate Roll and Pitch at Sea8 citations · 2022
- 6DANAE++: A Smart Approach for Denoising Underwater Attitude Estimation6 citations · 2021
- 7DANAE: a denoising autoencoder for underwater attitude estimation4 citations · 2020