most citedUW-MARL: Multi-Agent Reinforcement Learning for Underwater Adaptive Sampling using Autonomous Vehicles

13 citations · 24 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY201913 cited

UW-MARL: Multi-Agent Reinforcement Learning for Underwater Adaptive Sampling using Autonomous Vehicles

Mehdi Rahmati, Mohammad Nadeem, Vidyasagar Sadhu +1

Near-real-time water-quality monitoring in uncertain environments such as rivers, lakes, and water reservoirs of different variables is critical to protect the aquatic life and to…

eess.IV20199 cited

Real-time Image Enhancement for Vision-based Autonomous Underwater Vehicle Navigation in Murky Waters

Wenjie Chen, Mehdi Rahmati, Vidyasagar Sadhu +1

Classic vision-based navigation solutions, which are utilized in algorithms such as Simultaneous Localization and Mapping (SLAM), usually fail to work underwater when the water is…

eess.SP20192 cited

Compressed Underwater Acoustic Communications for Dynamic Interaction with Underwater Vehicles

Mehdi Rahmati, Archana Arjula, Dario Pompili

Underwater vehicles are utilized in various applications including underwater data-collection missions. The tethered connection constrains the mission both in distance traveled and…

eess.SP2019

UW-SVC: Scalable Video Coding Transmission for In-network Underwater Imagery Analysis

Mehdi Rahmati, Dario Pompili

Underwater imagery has enabled numerous civilian applications in various domains, ranging from academia to industry, and from industrial surveillance and maintenance to environment…

eess.SP2019

In-network Collaboration for CDMA-based Reliable Underwater Acoustic Communications

Mehdi Rahmati, Roberto Petroccia, Dario Pompili

Achieving high throughput and reliability in underwater acoustic networks for transmitting distributed and large volume of data is a challenging task due to the bandwidth-limited a…