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Aaron Marburg

Principal Electrical/Computer Engineer

Email

amarburg@apl.washington.edu

Phone

206-685-8461

Biosketch

Dr. Marburg's research focuses on the development of robotic platforms for ocean exploration and science, with a focus on perception, situational awareness, and mission planning. He also has a background in remote sensing, photogrammetry and precision navigation, and a strong interest in human-machine interfaces, and data and metadata management. He has over 15 years experience in electrical and software design for robotics, scientific instrumentation and high-performance computing. Dr. Marburg joined APL-UW as a SEED postdoctoral researcher in 2015 after completing his Ph.D. at the University of Canterbury in Christchurch, New Zealand.

Department Affiliation

Ocean Engineering

Education

B.S. Engineering, Swarthmore College, 1998

M.S. Aeronautical & Astronautical Engineering, Stanford University, 2004

Ph.D. Electrical & Computer Engineering, Canterbury University, 2015

Publications

2000-present and while at APL-UW

Report of the Resident AUV Workshop, 9–11 May 2018.

Delaney, J.B., D.A. Manalang, A. Marburg, A. Nawaz, and K. Daly, "Report of the Resident AUV Workshop, 9–11 May 2018." Technical Report APL-UW TR 1901, Applied Physics Laboratory, University of Washington, Seattle, 84 pp.

More Info

27 Mar 2020

Workshop participants divided into focus groups to consider resident autonomous undersea vehicle (R-AUV) use cases related to these four application areas: mid-ocean ridges and the overlying water column; gas hydrates and coastal oceans; polar, under-ice, and off-planet oceans; and maintenance and operation of installations.

The following technical elements emerged as clear common themes across R-AUV deployment scenarios: power and data management sub-systems, communications, navigation, capable sensor and payload systems, advanced autonomy functions. The single most important conclusion of the workshop is that incremental technological steps toward realizing routine R-AUV operations could yield revolutionary scientific and operational value.

Cloud-accelerated analysis of subsea high-definition camera data

Marburg, A., T.J. Crone, and F. Knuth, "Cloud-accelerated analysis of subsea high-definition camera data," Proc., OCEANS, 18-21 September, Anchorage, AK, 6 pp. (IEEE, 2017).

More Info

18 Sep 2017

The seafloor high-definition camera (CamHD) installed on the Ocean Observatories Initiative (OOI) Cabled Array (CA) provides real-time video of the Mushroom vent at the ASHES hydrothermal field in the Axial Volcano caldera on the Juan de Fuca spreading zone (Figure 1). CamHD performs a pre-programmed 13-minute motion sequence every 3 hours. The video captured during this sequence is stored as a 13GB HD video file in the OOI Cyber-Infrastructure (CI) at Rutgers University. As of July 2017 there are approx. 6700 videos in the CI, all of which are publicly accessible through a conventional HTTP interface. Unfortunately, it is impractical for a researcher (and taxing on the CI bandwidth) to download, store, and process the extent of the video archive for analysis. We describe two elements of our efforts to accelerate CamHD video analysis: a cloud-hosted application which provides a simplified interface for extracting individual frames from CamHD videos in a time- and bandwidth-efficient manner; and a tool for the automatic isolation and identification of video subsets showing a sequence of known camera positions. Automatic identification of these video segments allows rapid and automatic development of e.g., time lapse videos.

Using the OOI cabled array HD camera to explore geophysical and oceanographic problems at Axial Seamount

Crone, T.J., F. Knuth, and A. Marburg, "Using the OOI cabled array HD camera to explore geophysical and oceanographic problems at Axial Seamount," AGU Fall Meeting, 12-16 December, San Francisco, CA, OS41C-1970 (AGU, 2016).

More Info

15 Dec 2016

A broad array of Earth science problems can be investigated using high-definition video imagery from the seafloor, ranging from those that are geological and geophysical in nature, to those that are biological and water-column related. A high-definition video camera was installed as part of the Ocean Observatory Initiative's core instrument suite on the Cabled Array, a real-time fiber optic data and power system that stretches from the Oregon Coast to Axial Seamount on the Juan de Fuca Ridge. This camera runs a 14-minute pan-tilt-zoom routine 8 times per day, focusing on locations of scientific interest on and near the Mushroom vent in the ASHES hydrothermal field inside the Axial caldera. The system produces 13 GB of lossless HD video every 3 hours, and at the time of this writing it has generated 2100 recordings totaling 28.5 TB since it began streaming data into the OOI archive in August of 2015.

Because of the large size of this dataset, downloading the entirety of the video for long timescale investigations is not practical. We are developing a set of user-side tools for downloading single frames and frame ranges from the OOI HD camera raw data archive to aid users interested in using these data for their research. We use these tools to download about one year's worth of partial frame sets to investigate several questions regarding the hydrothermal system at ASHES, including the variability of bacterial "floc" in the water-column, and changes in high temperature fluid fluxes using optical flow techniques. We show that while these user-side tools can facilitate rudimentary scientific investigations using the HD camera data, a server-side computing environment that allows users to explore this dataset without downloading any raw video will be required for more advanced investigations to flourish.

More Publications

Acoustics Air-Sea Interaction & Remote Sensing Center for Environmental & Information Systems Center for Industrial & Medical Ultrasound Electronic & Photonic Systems Ocean Engineering Ocean Physics Polar Science Center
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