Novel midwater ocean sampling shows that physiology dictates zooplankton distributions in submesoscale low oxygen features.

The achievable accuracy of bathymetric mapping in the deep ocean using robotic systems is most often limited by the available guidance or navigation information used to combine the measured sonar ranges during the map making process. This paper presents an algorithm designed to mitigate the affects of poor ground referenced navigation by applying the principles of map registration and pose filtering commonly used in simultaneous localization and mapping ͑SLAM͒ algorithms. The goal of the algorithm is to produce a self-consistent point cloud representation of the bottom terrain with errors that are on a scale similar to the sonar range resolution rather than any direct positioning measurement. The presented algorithm operates causally and utilizes sensor data that are common to instrumented underwater robotic vehicles used for mapping and scientific explorations. Real world results are shown for data taken on several expeditions with the JASON remotely operated vehicle ͑ROV͒. Comparisons are made between more standard mapping approaches and the proposed method is shown to significantly improve the map quality and reveal scene information that would have otherwise been obscured due to poor direct navigation information.

The goals of this field note are twofold. First, we detail the operations and discuss the results of the 2005 Chios ancient shipwreck survey. This survey was conducted by an international team of engineers, archaeologists and natural scientists off the Greek island of Chios in the northeastern Aegean Sea using an autonomous underwater vehicle (AUV) built specifically for high-resolution site inspection and characterization. Second, using the survey operations as context, we identify the specific challenges of adapting AUV technology for deep water archaeology and describe how our team addressed these challenges during the Chios expedition. After identifying the state-of-the-art in robotic tools for deep water archaeology, we discuss opportunities where new developments and research (e.g., AUV platforms, underwater imaging, remote sensing and navigation techniques) will improve rapid assessment of deep water archaeological sites. It is our hope that by reporting on the Chios field expedition we can both describe the opportunities that AUVs bring to fine resolution seafloor site surveys and elucidate future opportunities for collaborations between roboticists and ocean scientists.

The benthic communities of the deep insular shelf at the Hind Bank

No abstract