Trajectory design and implementation for multiple autonomous underwater vehicles based on ocean model predictions

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Genetic analysis reveals two stocks of skipjack tuna (Katsuwonus pelamis) in the north western Indian Ocean

Skipjack (SJT) (Katsuwonus pelamis) is a medium sized, pelagic, highly dispersive tuna species that occurs widely across tropical and subtropical waters. SJT constitute the largest tuna fishery in the Indian Ocean, and are currently managed as a single stock. Patterns of genetic variation in a mtDNA gene and 6 microsatellite loci were examined to test for stock structure in the northwestern Indian Ocean. 324 individuals were sampled from five major fishing grounds around Sri Lanka, and single sites in the Maldive Islands and the Laccadive Islands. Phylogenetic reconstruction of mtDNA revealed two coexisting divergent clades in the region. AMOVA (Analysis of Molecular Variance) of mtDNA data revealed significant genetic differentiation among sites (ΦST = 0.2029, P < 0.0001), also supported by SAMOVA results. AMOVA of microsatellite data also showed significant differentiation among most sampled sites (FST = 0.0256, P<0.001) consistent with the mtDNA pattern. STRUCTURE analysis of the microsatellite data revealed two differentiated stocks. While the both two marker types examined identified two genetic groups, microsatellite analysis indicates that the sampled SJT are likely to represent individuals sourced from discrete breeding grounds that are mixed in feeding grounds in Sri Lankan waters.

Encroachment: what cost a pool with ocean views?

In Shadbolt v Wise [2002] QSC 348 the applicants were seeking relief under s184 of the Property Law Act 1974 (Qld) in respect of an encroachment that they constructed on land belonging to the adjacent owner. The encroachment in question consisted of slightly less than one half of an elaborate pool and pool enclosure (the area of the encroachment being approximately 108 square metres). The land upon which the encroachment was situated was elevated with distant ocean views.

Persistent ocean monitoring with underwater gliders : adapting sampling resolution

Ocean processes are dynamic, complex, and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path, while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show significant improvements in data resolution and path reliability compared to previously executed sampling paths used in the respective regions.

Pseudoseeds : investigating long-distance, ocean seed dispersal with wireless sensors

Recent theoretical research has shown that ocean currents and wind interact to disperse seeds over long distances among isolated landmasses. Dispersal of seeds among isolated oceanic islands, by birds, oceans and man, is a well-known phenomenon, and many widespread island plants have traits that facilitate this process. Crucially, however, there have been no mechanistic vector-based models of long-distance dispersal for seeds among isolated oceanic islands based on empirical data. Here, we propose a plan to develop seed analogues, or pseudoseeds, fitted with wireless sensor technology that will enable high-fidelity tracking as they disperse across the ocean. The pseudoseeds will be precisely designed to mimic actual seed buoyancy and morphology enabling realistic and accurate, vector-based dispersal models of ocean seed dispersal over vast geographic scales.

Higher-order spectral analysis of nonlinear ocean surface gravity waves

Higher-order spectral analysis is used to detect the presence of secondary and tertiary forced waves associated with the nonlinearity of energetic swell observed in 8- and 13-m water depths. Higher-order spectral analysis techniques are first described and then applied to the field data, followed by a summary of the results.

Towards improving mission execution for autonomous gliders with an ocean model and Kalman filter

In this paper, we examine the use of a Kalman filter to aid in the mission planning process for autonomous gliders. Given a set of waypoints defining the planned mission and a prediction of the ocean currents from a regional ocean model, we present an approach to determine the best, constant, time interval at which the glider should surface to maintain a prescribed tracking error, and minimizing time on the ocean surface. We assume basic parameters for the execution of a given mission, and provide the results of the Kalman filter mission planning approach. These results are compared with previous executions of the given mission scenario.

Controlling Minimally-Actuated Vehicles for Applications in Ocean Observation

Establishing a persistent presence in the ocean with an AUV to observe temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we propose a strategy that utilizes ocean model predictions to increase the autonomy and control of Lagrangian or profiling floats for precisely this purpose. An A* planner is applied to a local controllability map generated from predictions of ocean currents to compute a path between prescribed waypoints that has the highest likelihood of successful execution. The control to follow the planned path is computed by use of a model predictive controller. This controller is designed to select the best depth for the vehicle to exploit ambient currents to reach the goal waypoint. Mission constraints are employed to simulate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, and show surprising results in the ability of a Lagrangian float to reach a desired location.

Extending persistent monitoring by combining ocean models and Markov decision processes

Ocean processes are complex and have high variability in both time and space. Thus, ocean scientists must collect data over long time periods to obtain a synoptic view of ocean processes and resolve their spatiotemporal variability. One way to perform these persistent observations is to utilise an autonomous vehicle that can remain on deployment for long time periods. However, such vehicles are generally underactuated and slow moving. A challenge for persistent monitoring with these vehicles is dealing with currents while executing a prescribed path or mission. Here we present a path planning method for persistent monitoring that exploits ocean currents to increase navigational accuracy and reduce energy consumption.

Submarine pyroclastic deposits formed at the Soufrière Hills volcano, Montserrat (1995–2003) : what happens when pyroclastic flows enter the ocean?

The Soufrière Hills volcano, Montserrat, West Indies, has undergone a series of dome growth and collapse events since the eruption began in 1995. Over 90% of the pyroclastic material produced has been deposited into the ocean. Sampling of these submarine deposits reveals that the pyroclastic flows mix rapidly and violently with the water as they enter the sea. The coarse components (pebbles to boulders) are deposited proximally from dense basal slurries to form steep-sided, near-linear ridges that intercalate to form a submarine fan. The finer ash-grade components are mixed into the overlying water column to form turbidity currents that flow over distances >30 km from the source. The total volume of pyroclastic material off the east coast of Montserrat exceeds 280 × 106 m3, with 65% deposited in proximal lobes and 35% deposited as distal turbidites.

An investigation on the accuracy of regional ocean models through field trials

Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.

‘Wide Atlantic Ocean’ : acting methods and cultural translation in mainstream theatre

A recent production of Nicholson’s Shadowlands at the Brisbane Powerhouse could have included two advertising lines: “Outspoken American-Jewish poet meets conservative British Oxford scholar” and “Emotive American Method trained actor meets contained British trained actor.” While the fusion of acting methodologies in intercultural acting has been discussed at length, little discussion has focussed on the juxtaposition of diverse acting styles in production in mainstream theatre. This paper explores how the permutation of American Method acting and a more traditional British conservatory acting in Crossbow’s August 2010 production of Shadowlands worked to add extra layers of meaning to the performance text. This sometimes inimical relationship between two acting styles had its beginnings in the rehearsal room and continued onstage. Audience reception to the play in post-performance discussions revealed the audience’s acute awareness of the transatlantic cultural tensions on stage. On one occasion, this resulted in a heated debate on cultural expression, continuing well after the event, during which audience members became co-performers in the cultural discourses of the play.

Diversity of dicotyledenous-infecting geminiviruses and their associated DNA molecules in Southern Africa, including the South-west Indian Ocean Islands

The family Geminiviridae comprises a group of plant-infecting circular ssDNA viruses that severely constrain agricultural production throughout the temperate regions of the world, and are a particularly serious threat to food security in sub-Saharan Africa. While geminiviruses exhibit considerable diversity in terms of their nucleotide sequences, genome structures, host ranges and insect vectors, the best characterised and economically most important of these viruses are those in the genus Begomovirus. Whereas begomoviruses are generally considered to be either monopartite (one ssDNA component) or bipartite (two circular ssDNA components called DNA-A and DNA-B), many apparently monopartite begomoviruses are associated with additional subviral ssDNA satellite components, called alpha- (DNA-αs) or betasatellites (DNA-βs). Additionally, subgenomic molecules, also known as defective interfering (DIs) DNAs that are usually derived from the parent helper virus through deletions of parts of its genome, are also associated with bipartite and monopartite begomoviruses. The past three decades have witnessed the emergence and diversification of various new begomoviral species and associated DI DNAs, in southern Africa, East Africa, and proximal Indian Ocean islands, which today threaten important vegetable and commercial crops such as, tobacco, cassava, tomato, sweet potato, and beans. This review aims to describe what is known about these viruses and their impacts on sustainable production in this sensitive region of the world. © 2012 by the authors licensee MDPI, Basel, Switzerland.

Controlling buoyancy-driven profiling floats for applications in ocean observation

Establishing a persistent presence in the ocean with an autonomous underwater vehicle (AUV) capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of vehicles that can only control their depth in the water column for such extended deployments. We present a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy and enables general control for these profiling floats. The proposed method is based on experimentally validated techniques for utilizing ocean current models to control autonomous gliders. With the appropriate vertical actuation, and utilizing spatio–temporal variations in water speed and direction, we show that general controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution. A computed depth plan is generated with a model-predictive controller (MPC), and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA, USA, that show encouraging results in the ability of a drifting vehicle to reach a desired location.