Peggy P. Li

Planning and Implementing Trajectories for Autonomous Underwater Vehicles to Track Evolving Ocean Processes Based on Predictions from a Regional Ocean Model

Path planning and trajectory design for autonomous underwater vehicles (AUVs) is of great importance to the oceanographic research community because automated data collection is becoming more prevalent. Intelligent planning is required to maneuver a vehicle to high-valued locations to perform data collection. In this paper, we present algorithms that determine paths for AUVs to track evolving features of interest in the ocean by considering the output of predictive ocean models. While traversing the computed path, the vehicle provides near-real-time, in situ measurements back to the model, with the intent to increase the skill of future predictions in the local region. The results presented here extend preliminary developments of the path planning portion of an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. This extension is the incorporation of multiple vehicles to track the centroid and the boundary of the extent of a feature of interest. Similar algorithms to those presented here are under development to consider additional locations for multiple types of features. The primary focus here is on algorithm development utilizing model predictions to assist in solving the motion planning problem of steering an AUV to high-valued locations, with respect to the data desired. We discuss the design technique to generate the paths, present simulation results and provide experimental data from field deployments for tracking dynamic features by use of an AUV in the Southern California coastal ocean.

Autonomous Underwater Vehicle trajectory design coupled with predictive ocean models: A case study

Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceanographic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to maneuver through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.

Spatiotemporal path planning in strong, dynamic, uncertain currents

This work addresses mission planning for autonomous underwater gliders based on predictions of an uncertain, time-varying current field. Glider submersibles are highly sensitive to prevailing currents so mission planners must account for ocean tides and eddies. Previous work in variable-current path planning assumes that current predictions are perfect, but in practice these forecasts may be inaccurate. Here we evaluate plan fragility using empirical tests on historical ocean forecasts for which followup data is available. We present methods for glider path planning and control in a time-varying current field. A case study scenario in the Southern California Bight uses current predictions drawn from the Regional Ocean Monitoring System (ROMS).

Trajectory design for autonomous underwater vehicles based on ocean model predictions for feature tracking

Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection.We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to themodel to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks.We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.

Accessing and visualizing scientific spatiotemporal data

This paper discusses work done by JPLs Parallel Applications Technologies Group in helping scientists access and visualize very large data sets through the use of multiple computing resources, such as parallel supercomputers, clusters, and grids. These tools do one or more of the following tasks: visualize local data sets for local users, visualize local data sets for remote users, and access and visualize remote data sets. The tools are used for various types of data, including remotely sensed image data, digital elevation models, astronomical surveys, etc. The paper attempts to pull some common elements out of these tools that may be useful for others who have to work with similarly large data sets.

Data-Oriented distributed computing for science: reality and possibilities

As is becoming commonly known, there is an explosion happening in the amount of scientific data that is publicly available One challenge is how to make productive use of this data This talk will discuss some parallel and distributed computing projects, centered around virtual astronomy, but also including other scientific data-oriented realms It will look at some specific projects from the past, including Montage, Grist, OurOcean, and SCOOP, and will discuss the distributed computing, Grid, and Web-service technologies that have successfully been used in these projects.

Parallel Computation and Visualization of 3D, Time-Dependent, Thermal Convective Flows

A high-resolution numerical study on parallel systems is reported on three-dimensional (3D), time-dependent, thermal convective flows. Numerical results are obtained for Rayleigh numbers up to 5×107 and for a Prandtl number 0.733 equivalent to that of air, in a cubical enclosure, which is heated differentially at two vertical sidewalls. A parallel implementation of the finite volume method with a multigrid scheme is discussed, and a parallel and distributed visualization system is developed for visualizing the flow. The details of the 3D, time-dependent flow are described. Separations of the flow near the horizontal walls occur, and y-variations of the flow are strong. Periodical flow patterns appear. The 3D solutions for such high Rayleigh number 5×107 become strong convective, time-dependent, and periodical.

Identification of differential pharyngeal cytokine profiles during HIV infection

Background Significantly higher pharyngeal shedding of Epstein-Barr virus (EBV) is observed during HIV infection. Increased EBV shedding in pharynx is not affected even during highly active antiretroviral theyrapy (HAART). EBV positive monocyte populations have been shown to carry EBV to pharyngeal mucosa. Human cytokine profiles are often altered to facilitate herpes virus infection. Thus pharyngeal cytokine profiles may influence EBV reactivation and shedding during HIV infection. Our objective was to compare 37 pharyngeal cytokine profiles of HIV-seropositive patients who were or were not receiving HAART therapy.