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

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

Goby-Acomms version 2: extensible marshalling, queuing, and link layer interfacing for acoustic telemetry

We present the Goby-Acomms project version 2 (Goby2) which provides software for communication amongst autonomous marine vehicles over extremely bandwidth-constrained links. Goby2's modular design provides four discrete yet interoperable components: 1) physics- oriented marshalling via the Dynamic Compact Control Language (DCCL); 2) dynamic priority queuing; 3) time division multiple access (TDMA) medium access control (MAC); 4) and an extensible link-layer interface (ModemDriver). Keywords: Communication protocols; autonomous vehicles; marine systems; telemetry; source codin

The Dynamic Compact Control Language: A compact marshalling scheme for acoustic communications

The Dynamic Compact Control Language (DCCL) extends the ubiquitous Extensible Markup Language (XML) to provide a structure for defining very short messages comprised of bounded basic variable types, suitable for transmission over a low throughput acoustic channel. Algorithms are provided to consistently encode and decode the fields of these messages, and an implementation of DCCL with encryption is provided as a open source C++ library. Furthermore, DCCL has been incorporated into a publish/subscribe robotic autonomy architecture and used on numerous simulations and field trials involving heterogeneous networks of vehicles; we present the results of several. The ease of reconfiguration and error checking provided by DCCL make it well suited for collaborative autonomous underwater vehicle operations, where the flexibility to quickly change the message set, combined with low incidence of error, is necessary for success.United States. Office of Naval Research (project N00014-08-1-0011)United States. Office of Naval Research (project N00014-08-1- 0013

Cooperative autonomy for contact investigation

Autonomous surface and underwater vehicles present a safe and low-cost solution for various contact investigation tasks, such as harbor surveillance for potentially threatening small craft or submarines. Since such a task may involve many contacts of interest, such as all the normal boat traffic in a busy harbor, a single unmanned surface vehicle (USV) is unlikely to be able to reasonably investigate all the contacts. Instead, multiple USVs can be deployed to investigate contacts simultaneously. In this paper we present a system that performs this task using the MOOS-IvP autonomy infrastructure. The approach is analogous to “zone defense” in basketball, and only requires that each vehicle have knowledge of its collaborators' positions. The resulting network requires only requires a small amount of communication data to be transmitted, making it applicable in the often low-throughput ocean environment.United States. Office of Naval ResearchNATO Undersea Research Centre Visiting Research Programm