With the advent of Autonomous Underwater Vehicles (AUVs) and other mobile platforms, marine robotics have had substantial impact on the oceanographic sciences. These systems have allowed scientists to collect data over temporal and spatial scales that would be logistically impossible or prohibitively expensive using traditional ship-based measurement techniques. Increased dependence of scientists on such robots has permeated scientific data gathering with future field campaigns involving these platforms as well as on entire infrastructure of people, processes and software, on shore and at sea. Recent field experiments carried out with a number of surface and underwater platforms give clues to how these technologies are coalescing and need to work together. We highlight one such confluence and describe a future trajectory of needs and desires for field experiments with autonomous marine robotic platforms. Our 2010 inter-disciplinary experiment in the Monterey Bay involved multiple platforms and collaborators with diverse science goals. One important goal was to enable situational awareness, planning and collaboration before, during and after this large-scale collaborative exercise. We present the overall view of the experiment and describe an important shore-side component, the Oceanographic Decision Support System (ODSS), its impact and future directions leveraging such technologies for field experiments.

In this paper, we present a technological development of an autonomous underwater vehicle (AUV) docking system motivated by science requirements. Twenty-seven case studies were drafted after having elaborate discussions with twelve senior marine scientists from a wide range of oceanographic fields including physical oceanography, ocean chemistry, midwater ecology, biological oceanography, molecular biology, marine microbiology, geology, evolutionary biology, and benthic ecology. These science cases spread over coastal ocean, deep-ocean, mid-ocean ridge, and polar regions. All of these science missions can be significantly benefited from new and improved sets of data and samples that will be collected by using a docked AUV. The case studies are organized to address the science issue, significance of the problem, required data and measurements to address the scientific importance, a non-docked method for acquiring data, and the benefit of using a docked AUV. More than twenty science instruments (in addition to navigational sensors) are identified and evaluated for these science missions. Science pay loads for the AUV and the docking system are discussed in detail. Functional requirements for a general purpose docking system are identified and pros and cons of various docking subsystems are explained. A fuzzy logic based solution approach for an autonomous docking system design and development is also proposed in this paper.

The ocean, is fundamentally important to many areas of modern society and thus improved knowledge of the ocean is essential. Ocean scientists have made remarkable progress in observation technology, modeling and assimilation in physical oceanography, acoustics, and biology. To some extent, such advances have been confined to each discipline. Therefore a great demand has arisen for a modern distributed computing and networking infrastructure within which we bring together advanced modeling, observation tools and field estimation methods. The paper describes a knowledge network of distributed heterogeneous data and software resources for multidisciplinary ocean research.

Navigation is a critical requirement for the operation of autonomous underwater vehicles (AUVs). In this paper we present acoustic navigation results for the Odyssey II AUV obtained by using a Kalman filter that integrates dead-reckoning with acoustic range measurements made to an array of acoustic beacons pre-deployed in the operating environment. Because spurious acoustic measurements due to multipath propagation are common, initialization and outlier rejection techniques are addressed. The navigation algorithm has been extensively tested by post-processing of real data acquired by Odyssey II during field operations in a variety of environments. These include the Charles River Basin, the Atlantic Ocean (1.5 km off the Florida coast), and the Pacific Ocean (375 km off the Oregon coast). Our results show improved performance over prior techniques based exclusively on fix computation and dead reckoning.