The Information Content of Ocean Noise: Theory and Experiment
Imaging the Changing Arctic with Ice Noise

Climate-related variations in the Arctic Ocean affect the composition of the ice cover, such as its thickness and age, as well as the acoustic properties of the water layer. These changes in the environment influence the signals produced by events such as ice ridging or cracking, and have a significant impact in underwater acoustic communication and navigation. By analyzing recordings of ocean noise, more accurate models of the Arctic environment may be created.

A project of the Multidisciplinary University Research Initiative (MURI), in collaboration with the University of California-San Diego (UCSD) and the Office of Naval Research (ONR)

Sponsors & Parnters:
Office of Naval Research
University of California - San Diego

Related work:

The new Arctic:
Environmentally Adaptive Acoustic Communication and Navigation

The MIT operation of a BF21 with a towed array in ICEX16 demonstrated the severe under-ice acoustic environment created by the climate related enhancement of the Beaufort Lens, a warm water lens entering from the Bering Strait, and which is neutrally buoyant at 75 m depth, creating a distinct double-duct, which requires underwater vehicles to be environmentally adaptive for maintaining acoustic connectivity.

This project, developed in collaboration with the Office of Naval Research (ONR), seeks to develop tools and frameworks that will provide autonomous underwater vehicles the needed environmentally adaptive capabilities.

Office of Naval Research

Related work:

Unmanned Marine Vehicles:
Multi-Vehicle Cooperative and Adaptive Autonomy Algorithms

A project developed in collaboration with the Battelle Memorial Institute

Battelle Memorial Institute

Related work:

Aquaticus: A Collaborative Human-Machine Robotic Competition

A project with the goal of developing a competition where humans and robots compete together against similarly configured teams of humans and robots. The competition is conducted on the water in about a one square kilometer area off the MIT Sailing Pavilion.
This research aims to explore a relatively poorly understood intersection of two well known areas of robotic systems research: the (embedded) human-robot interface and multi-robot zero-sum competitions. The intersection is created by embedding humans alongside robots, as equal teammates, on a playing field competing against a similarly configured team. Autonomy algorithm design and human robot communications will be re-considered from the perspective of the situated human who will be dealing with stress, uncertainty and pressures of performing their own role in the competition, in coordination with their robot teammates.

A project developed in collaboration with the Office of Naval Research (ONR)


Office of Naval Research

Related work:

Track and Trail of a Towed Acoustic Source using a Small AUV

The Bluefin SandShark is a small, one-person portable autonomous underwater vehicle (AUV) manufactured by Bluefin Robotics. The platform comes with a standardized tailcone section, which houses the propeller motor and fin actuation system, battery, an altimeter and pressure/depth sensor, a MEMS IMU, and an antenna for GPS and WiFi.

Our payload section was jointly designed by LAMSS and Bluefin. The payload includes a tetrahedral hydrophone array at the nose end of the vehicle, acoustic data acquisition system, and a computer for autonomy and real-time signal processing. The tetrahedral array gives the vehicle the ability to localize an acoustic source in real time for navigation or tracking. Data recording from the array is triggered by a Chip Scale Atomic clock (CSAC) providing precise time synchronization. A beaglebone black computer runs MOOS-IvP for back-seat autonomy. The vehicle will soon also have an acoustic modem for communications while submerged.

We are currently in the process of integrating a rev. 2 WHOI acoustic micromodem for vehicle command and monitoring. The entire vehicle stands at a length and diameter of approximately 125cm by 12.5cm.

Recent experiments have focussed on troubleshooting and fine-tuning the software interface between the frontseat (tailcone section) and backseat (payload section), which allows navigation estimates to be passed from, and control commands to be passed to, the frontseat from the backseat. These tests have successfully demonstrated the external control of the vehicle from our payload, using custom behaviours specified using the LAMSS MOOS-IvP autonomy framework to prosecute user-specified missions. In addition, we are currently using data gathered by the acoustic array to investigate how well the vehicle is able to localize a fixed acoustic pinger - the CSAC allows the vehicle to maintain a precise GPS-synced PPS signal, providingaccurate acoustic range measurements to the GPS-synced acoustic source, while acoustic beamforming and signal-processing allows the calculation of azimuth and elevation angle estimates. The near-term goal is to use these relative range and angle estimates to track and trail an acoustic source that is being towed by one of the LAMSS M200 ASCs.

In the future we hope to use multiple SandShark AUVs with similar acoustic arrays to perform multi-AUV formation control using relative range and bearing measurements. In addition, future work includes the use of our current SandShark equipped with an acoustic line array to characterise the acoustic signature of seabed-lying metallic objects.

Battelle, Mr. Michael Mellott

The SandShark UUV was donated under a DARPA/Bluefin development program.

GOATS - Generic Ocean Array Technology Systems

The GOATS project, initiated in 1998 in collaboration between MIT and NURC, with the long-term objective of developing net-centric, autonomous underwater vehicle sensing concepts for littoral MCM and ASW. The core of the program is the exploitation of collaborative and environmentally adaptive, bi- and multi-static, passive and active sonar configurations for concurrent detection, classification and localization of subsea and bottom objects. A principal development has been the MOOS-IvP Nested Autonomy concept with onboard integrated acoustic sensing, signal processing and platform control algorithms for adaptive, collaborative, multiplatform REA, MCM, and ASW in unknown and unmapped littoral environments with uncertain navigation and communication infrastructure.

The MOOS autonomy middleware was developed under GOATS in 2001-02 by Paul Newman while he was holding a Post-doc appointment at MIT, and all autonomous vehicles operated by the lab are using MOOS. Another development under GOATS has been a nested, distributed command and control architecture that enables individual network nodes of clusters of nodes to complete the mission objectives, including target detection, classification, localization and tracking (DCLT), fully autonomously with no or limited communication with the network operators. The need for such a nested, autonomous communication, command and control architecture has become clear from the series of experiments carried out in the past under GOATS and several experiments carried out under the ONR UPS PLUSNet program.

Office of Naval Research, Code 321OA (Dr. Bob Headrick, Program Manager)
Office of Naval Research, Code 321OE (Dr. Jason Stack, Program Manager)

NATO Undersea Research Centre, LaSpezia, Italy

DSOP - Deep Sea Operations

The objective of this program is to develop a new capability for cost-effective wide-area, persistant acoustic surveillance in the deep ocean. MIT LAMSS is a partner in an industry-academia team developing an innovative acoustic surveillance concept based on a distributed network of autonomous underwater vehicles close to the bottom, operating a hybrid suite of passive and active acoustic sensors, exploiting the deep ocean environmental acoustics for optimal system performance. MIT LAMSS is responsible for developing a MOOS-IvP platform autonomy system that integrates the acoustic sensor processing with on-board environmental and tactical modeling to exploit vertical and horizontal mobility to achieve optimal DCLT performance and inter-node communication.

The MOOS-IvP platform autonomy is nested within a mission planning autonomy and communication, command and control infrastructure developed by the partners.

DARPA (Dr. Shelby Sullivan, Program manager)

Applied Physical Sciences (APS)
Scientific Systems Corporation Inc. (SSCI)
Bluefin Robotics
General Dynamics