Hunter C. Brown

An Overview of Autonomous Underwater Vehicle Research and Testbed at PeRL

This article provides a general overview of the autonomous underwater vehicle (AUV) research thrusts being pursued within the Perceptual Robotics Laboratory (PeRL) at the University of Michigan. Founded in 2007, PeRL’s research centers on improving AUV autonomy via algorithmic advancements in environmentally based perceptual feedback for real-time mapping, navigation, and control. Our three major research areas are (1) real-time visual simultaneous localization and mapping (SLAM), (2) cooperative multi-vehicle navigation, and (3) perceptiondriven control. Pursuant to these research objectives, PeRL has developed a new multi-AUV SLAM testbed based upon a modified Ocean-Server Iver2 AUV platform. PeRL upgraded the vehicles with additional navigation and perceptual sensors for underwater SLAM research. In this article, we detail our testbed development, provide an overview of our major research thrusts, and put into context how our modified AUV testbed enables experimental real-world validation of these algorithms.

Development of a multi-AUV SLAM testbed at the University of Michigan

This paper reports the modifications involved in preparing two commercial Ocean-Server AUV systems for simultaneous localization and mapping (SLAM) research at the University of Michigan (UMich). The UMich Perceptual Robotics Laboratory (PeRL) upgraded the vehicles with additional navigation and perceptual sensors including 12-bit stereo down-looking Prosilica cameras, a Teledyne 600 kHz RDI Explorer DVL for 3-axis bottom-lock velocity measurements, a KVH single-axis fiber-optic gyroscope for yaw rate, and a WHOI Micromodem for communication, along with other sensor packages discussed forthwith. To accommodate the additional sensor payload, a new Delrin nose cone was designed and fabricated. Additional 32-bit embedded CPU hardware was added for data-logging, real-time control, and in-situ real-time SLAM algorithm testing and validation. Details of the design modification, and related research enabled by this integration effort, are discussed herein.

BathyBoat: An Autonomous Surface Vessel for Stand-alone Survey and Underwater Vehicle Network Supervision

Exploration of remote environments can now be conducted in relative safety using unmanned vehicles. This article describes the joint University of Michigan and Michigan Tech Research Institute project to design and build a new autonomous surface vessel (ASV) for use in research, education, and resource management as well as in the commercial sector. The article highlights relevant real world testing and recent missions involving the BathyBoat ASV on Alaskas North Slope, the harbors of Illinois, and various riverine environments in Michigan.

An overview of AUV algorithms research and testbed at the University of Michigan

This paper provides a general overview of the autonomous underwater vehicle (AUV) research projects being pursued within the Perceptual Robotics Laboratory (PeRL) at the University of Michigan. Founded in 2007, PeRLs research thrust is centered around improving AUV autonomy via algorithmic advancements in sensor-driven perceptual feedback for environmentally-based real-time mapping, navigation, and control. In this paper we discuss our three major research areas of: (1) real-time visual simultaneous localization and mapping (SLAM); (2) cooperative multi-vehicle navigation; and (3) perception-driven control. Pursuant to these research objectives, PeRL has acquired and significantly modified two commercial off-the-shelf (COTS) Ocean-Server Technology, Inc. Iver2 AUV platforms to serve as a real-world engineering testbed for algorithm development and validation. Details of the design modification, and related research enabled by this integration effort, are discussed herein.

The Upper-Great Lakes Observing System

This paper reports an overview of the University of Michigans Upper-Great Lakes Observing System (U-GLOS) program, as well as the design, construction, and testing of offshore buoy platforms, communication schemes, and a shore-based server system. Since 2003, the University of Michigans Marine Hydrodynamics Laboratories (MHL) has partnered with local communities, as well as Northwestern Michigans College Water Studies Institute, DTE, Alliance for Coastal Technologies, Michigan Sea Grant, and the Grand Traverse Band of Ottawa and Chippewa Indians to develop the U-GLOS program that exists today. The U-GLOS program now includes both land and offshore platforms that monitor environmental conditions and report, in real-time, the results to a publicly accessible web site. Each station measures a wide range of properties including air temperature, wind speed, wind gusts, solar radiation, humidity, and more. Buoy stations also measure water temperature (thermistor array), directional and non-directional wave characteristics. Ongoing scientific and engineering research is discussed, as well as an overview of available data products, quality control and quality assurance algorithms, and conformity to the National Data Buoy Center (NDBC) standards.

Auto-tuning mother nature: Waves in music and water

In the late 1990s, the application of a well known mathematical transformation revolutionized the music industry. That process, known as Auto-Tune, relies on the ability of the Fourier Transform to identify dominant frequencies within a time-series record of a signal. Mega-stars like Madonna, Cher, Britney Spears, Tim McGraw, Kanye West, and many more heavily use Auto-Tune not only to ensure perfect pitch, but often simply for the unique sounds the function produces. Perhaps unknown to these singers, wave experts were using exactly the same mathematical functions to identify ocean wave characteristics forty years prior to the first mainstream music hit (Chers “Believe”) to use Auto-Tune. This paper presents an overview of the Fourier Transform and its application in both the music industry and the scientific study of water waves.