Adaptable underwater networks: The relation between autonomy and communications

This paper discusses requirements for autonomy and communications in maritime environments through two use cases which are sourced from military scenarios: Mine Counter Measures (MCM) and Anti-Submarine Warfare (ASW). To address these requirements, this work proposes a service-oriented architecture that breaks the typical boundaries between the autonomy and the communications stacks. An initial version of the architecture has been implemented and its deployment during a field trial done in January 2019 is reported. The paper discusses the achieved results in terms of system flexibility and ability to address the MCM and ASW requirements

Unified command and control for heterogeneous marine sensing networks

Successful command and control (C2) of autonomous vehicles poses challenges that are unique to the marine environment, primarily highly restrictive acoustic communications throughput. To address this, the Unified C2 architecture presented here uses a highly compressed short message encoding scheme (Dynamic Compact Control Language or DCCL) to transfer commands and receive vehicle status. DCCL is readily reconfigurable to provide the flexibility needed to change commands on short notice. Furthermore, operation of multiple types of vehicles requires a C2 architecture that is both scalable and flexible to differences among platform hardware and abilities. The Unified C2 architecture uses the MOOS-IvP autonomy system to act as a “backseat driver” of the vehicle. This provides a uniform interface to the control system on all the vehicles. Also, a hierarchical configuration system is used to allow single changes in configuration to propagate to all vehicles in operation. Status data from all vehicles are displayed visually using Google Earth, which also allows a rapid meshing of data from other sources (sensors, automatic identification system, radar, satellites) from within, as well as outside of, the MOOS-IvP architecture. Results are presented throughout from the CCLNET08, SQUINT08, GLINT08, GLINT09, SWAMSI09, and DURIP09 experiments involving robotic marine autonomous surface craft (ASCs) and Bluefin, OceanServer, and NATO Undersea Research Centre (NURC) autonomous underwater vehicles (AUVs).United States. Office of Naval Research (Grant N00014-1-08-1-0013)United States. Office of Naval Research (Grant N00014-1-08-1-0011

Advances in integrating autonomy with acoustic communications for intelligent networks of marine robots

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2013Autonomous marine vehicles are increasingly used in clusters for an array of oceanographic tasks. The effectiveness of this collaboration is often limited by communications: throughput, latency, and ease of reconfiguration. This thesis argues that improved communication on intelligent marine robotic agents can be gained from acting on knowledge gained by improved awareness of the physical acoustic link and higher network layers by the AUV’s decision making software. This thesis presents a modular acoustic networking framework, realized through a C++ library called goby-acomms, to provide collaborating underwater vehicles with an efficient short-range single-hop network. goby-acomms is comprised of four components that provide: 1) losslessly compressed encoding of short messages; 2) a set of message queues that dynamically prioritize messages based both on overall importance and time sensitivity; 3) Time Division Multiple Access (TDMA) Medium Access Control (MAC) with automatic discovery; and 4) an abstract acoustic modem driver. Building on this networking framework, two approaches that use the vehicle’s “intelligence” to improve communications are presented. The first is a “non-disruptive” approach which is a novel technique for using state observers in conjunction with an entropy source encoder to enable highly compressed telemetry of autonomous underwater vehicle (AUV) position vectors. This system was analyzed on experimental data and implemented on a fielded vehicle. Using an adaptive probability distribution in combination with either of two state observer models, greater than 90% compression, relative to a 32-bit integer baseline, was achieved. The second approach is “disruptive,” as it changes the vehicle’s course to effect an improvement in the communications channel. A hybrid data- and model-based autonomous environmental adaptation framework is presented which allows autonomous underwater vehicles (AUVs) with acoustic sensors to follow a path which optimizes their ability to maintain connectivity with an acoustic contact for optimal sensing or communication.I wish to acknowledge the sponsors of this research for their generous support of my tuition, stipend, and research: the WHOI/MIT Joint Program, the MIT Presidential Fellowship, the Office of Naval Research (ONR) # N00014-08-1-0011, # N00014-08-1-0013, and the ONR PlusNet Program Graduate Fellowship, the Defense Advanced Research Projects Agency (DARPA) (Deep Sea Operations: Applied Physical Sciences (APS) Award # APS 11-15 3352-006, APS 11-15-3352-215 ST 2.6 and 2.7

Underwater radio frequency image sensor using progressive image compression and region of interest

The increasing demand for underwater robotic intervention systems around the world in several application domains requires more versatile and inexpensive systems. By using a wireless communication system, supervised semi-autonomous robots have freedom of movement; however, the limited and varying bandwidth of underwater radio frequency (RF) channels is a major obstacle for the operator to get camera feedback and supervise the intervention. This paper proposes the use of progressive (embedded) image compression and region of interest (ROI) for the design of an underwater image sensor to be installed in an autonomous underwater vehicle, specially when there are constraints on the available bandwidth, allowing a more agile data exchange between the vehicle and a human operator supervising the underwater intervention. The operator can dynamically decide the size, quality, frame rate, or resolution of the received images so that the available bandwidth is utilized to its fullest potential and with the required minimum latency. The paper focuses first on the description of the system, which uses a camera, an embedded Linux system, and an RF emitter installed in an OpenROV housing cylinder. The RF receiver is connected to a computer on the user side, which controls the camera monitoring parameters, including the compression inputs, such as region of interest (ROI), size of the image, and frame rate. The paper focuses on the compression subsystem and does not attempt to improve the communications physical media for better underwater RF links. Instead, it proposes a unified system that uses well-integrated modules (compression and transmission) to provide the scientific community with a higher-level protocol for image compression and transmission in sub-sea robotic interventions

Progressively communicating rich telemetry from autonomous underwater vehicles via relays

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2012As analysis of imagery and environmental data plays a greater role in mission construction and execution, there is an increasing need for autonomous marine vehicles to transmit this data to the surface. Without access to the data acquired by a vehicle, surface operators cannot fully understand the state of the mission. Communicating imagery and high-resolution sensor readings to surface observers remains a significant challenge – as a result, current telemetry from free-roaming autonomous marine vehicles remains limited to ‘heartbeat’ status messages, with minimal scientific data available until after recovery. Increasing the challenge, longdistance communication may require relaying data across multiple acoustic hops between vehicles, yet fixed infrastructure is not always appropriate or possible. In this thesis I present an analysis of the unique considerations facing telemetry systems for free-roaming Autonomous Underwater Vehicles (AUVs) used in exploration. These considerations include high-cost vehicle nodes with persistent storage and significant computation capabilities, combined with human surface operators monitoring each node. I then propose mechanisms for interactive, progressive communication of data across multiple acoustic hops. These mechanisms include wavelet-based embedded coding methods, and a novel image compression scheme based on texture classification and synthesis. The specific characteristics of underwater communication channels, including high latency, intermittent communication, the lack of instantaneous end-to-end connectivity, and a broadcast medium, inform these proposals. Human feedback is incorporated by allowing operators to identify segments of data thatwarrant higher quality refinement, ensuring efficient use of limited throughput. I then analyze the performance of these mechanisms relative to current practices. Finally, I present CAPTURE, a telemetry architecture that builds on this analysis. CAPTURE draws on advances in compression and delay tolerant networking to enable progressive transmission of scientific data, including imagery, across multiple acoustic hops. In concert with a physical layer, CAPTURE provides an endto- end networking solution for communicating science data from autonomous marine vehicles. Automatically selected imagery, sonar, and time-series sensor data are progressively transmitted across multiple hops to surface operators. Human operators can request arbitrarily high-quality refinement of any resource, up to an error-free reconstruction. The components of this system are then demonstrated through three field trials in diverse environments on SeaBED, OceanServer and Bluefin AUVs, each in different software architectures.Thanks to the National Science Foundation, and the National Oceanic and Atmospheric Administration for their funding of my education and this work

The GLINT10 field trial results

Autonomous underwater vehicles (AUVs) have gained more interest in recent years for military as well as civilian applications. One potential application of AUVs is for the purpose of undersea surveillance. As research into undersea surveillance using AUVs progresses, issues arise as to how an AUV acquires, acts on, and shares information about the undersea battle space. These issues naturally touch on aspects of vehicle autonomy and underwater communications, and need to be resolved through a spiral development process that includes at sea experimentation. This paper presents a recent AUV implementation for active anti-submarine warfare tested at sea in the summer of 2010. On-board signal processing capabilities and an adaptive behavior are discussed in both a simulation and experimental context. The implications for underwater surveillance using AUVs are discussed

Maritime Data Transfer Protocol (MDTP): A Proposal for a Data Transmission Protocol in Resource-Constrained Underwater Environments Involving Cyber-Physical Systems

The utilization of autonomous maritime vehicles is becoming widespread in operations that are deemed too hazardous for humans to be directly involved in them. One of the ways to increase the productivity of the tools used during missions is the deployment of several vehicles with the same objective regarding data collection and transfer, both for the benefit of human staff and policy makers. However, the interchange of data in such an environment poses major challenges, such as a low bandwidth and the unreliability of the environment where transmissions take place. Furthermore, the relevant information that must be sent, as well as the exact size that will allow understanding it, is usually not clearly established, as standardization works are scarce in this domain. Under these conditions, establishing a way to interchange information at the data level among autonomous maritime vehicles becomes of critical importance since the needed information, along with the size of the transferred data, will have to be defined. This manuscript puts forward the Maritime Data Transfer Protocol, (MDTP) a way to interchange standardized pieces of information at the data level for maritime autonomous maritime vehicles, as well as the procedures that are required for information interchange.SWARMs (Smart and Networking Underwater Robots in Cooperation Meshes) 1034 European research project. It is under Grant Agreement 1035 n.662107-SWARMs-ECSEL-2014-1 and is being partially supported by the Spanish Ministry of Economy and Competitiveness (Ref: PCIN-2014-022-C02-02) and the ECSEL JU

Opportunistic Networks: Present Scenario- A Mirror Review

Opportunistic Network is form of Delay Tolerant Network (DTN) and regarded as extension to Mobile Ad Hoc Network. OPPNETS are designed to operate especially in those environments which are surrounded by various issues like- High Error Rate, Intermittent Connectivity, High Delay and no defined route between source to destination node. OPPNETS works on the principle of “Store-and-Forward” mechanism as intermediate nodes perform the task of routing from node to node. The intermediate nodes store the messages in their memory until the suitable node is not located in communication range to transfer the message to the destination. OPPNETs suffer from various issues like High Delay, Energy Efficiency of Nodes, Security, High Error Rate and High Latency. The aim of this research paper is to overview various routing protocols available till date for OPPNETs and classify the protocols in terms of their performance. The paper also gives quick review of various Mobility Models and Simulation tools available for OPPNETs simulation