Modeling and Inspection Applications of a Coastal Distributed Autonomous Sensor Network
Author(s)
Weymouth, Gabriel
Kurniawati, Hanna
Valdivia y Alvarado, Pablo
Taher, Tawfiq
Khan, Rubaina
Patrikalakis, Nicholas M
Leighton, Joshua C
Papadopoulos, Georgios
Date Issued
July 2012
Journal
ASME 2012 31st International Conference on Ocean, Offshore and Arctic Engineering: Volume 5: Ocean Engineering; CFD and VIV
Publisher
ASME International
Citation
Patrikalakis, Nicholas M., Joshua Leighton, Georgios Papadopoulos, Gabriel Weymouth, Hanna Kurniawati, Pablo Valdivia y Alvarado, Tawfiq Taher, and Rubaina Khan. “Modeling and Inspection Applications of a Coastal Distributed Autonomous Sensor Network.” ASME 2012 31st International Conference on Ocean, Offshore and Arctic Engineering: Volume 5: Ocean Engineering; CFD and VIV, 1-6 July 1, 2012, Rio de Janeiro, Brazil, ASME, 2012. © 2012 by ASME
Version
Final published version
Abstract
Real time in-situ measurements are essential for monitoring and understanding physical and biochemical changes within ocean environments. Phenomena of interest usually display spatial and temporal dynamics that span different scales. As a result, a combination of different vehicles, sensors, and advanced control algorithms are required in oceanographic monitoring systems. In this study our group presents the design of a distributed heterogeneous autonomous sensor network that combines underwater, surface, and aerial robotic vehicles along with advanced sensor payloads, planning algorithms and learning principles to successfully operate across the scales and constraints found in coastal environments. Examples where the robotic sensor network is used to localize algal blooms and collect modeling data in the coastal regions of the island nation of Singapore and to construct 3D models of marine structures for inspection and harbor navigation are presented. The system was successfully tested in seawater environments around Singapore where the water current is around 1-2m/s. Topics: Inspection , Modeling , Sensor networks , Shorelines
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1115/OMAE2012-83812
