Mapping and characterisation of the inter-reefal benthic assemblages of the Torres Strait

A comprehensive survey of the benthic assemblages of the Torres Strait was conducted in order to provide critical baseline information for regional marine planning, assessing the environmental sustainability of fisheries and understanding the ecosystems of the region. Over 150 sites throughout the region were sampled with a modified prawn trawl, towed underwater video, pipe dredge and epibenthic sled. This manuscript provides a broad overview of the activities undertaken and data collected. Two thousand three hundred and seventy-two different nominal species were sampled by the trawl and sled, only 728 by both gears. The towed video was not able to provide the same level of taxonomic resolution of epibenthic taxa, but was particularly useful in areas where the seabed was too rough to be sampled. Data from the trawl, sled and video were combined to characterise the epibenthic assemblages of the region. Data from the towed video was also used to provide a characterisation of the inter-reefal benthic habitats, which was then analysed in combination with physical covariate data to examine relationships between the two. Levels of mud and gravel in the sediments, trawling effort and seabed current stress were the covariates most significantly correlated with the nature of the seabed habitats.

Distributed Robotic Vision as a service

The vision sense of standalone robots is limited by line of sight and onboard camera capabilities, but processing video from remote cameras puts a high computational burden on robots. This paper describes the Distributed Robotic Vision Service, DRVS, which implements an on-demand distributed visual object detection service. Robots specify visual information requirements in terms of regions of interest and object detection algorithms. DRVS dynamically distributes the object detection computation to remote vision systems with processing capabilities, and the robots receive high-level object detection information. DRVS relieves robots of managing sensor discovery and reduces data transmission compared to image sharing models of distributed vision. Navigating a sensorless robot from remote vision systems is demonstrated in simulation as a proof of concept.

A novel approach to 6-DOF adaptive trajectory tracking control of an AUV in the presence of parameter uncertainties

In this paper, the trajectory tracking control of an autonomous underwater vehicle (AUVs) in six-degrees-of-freedom (6-DOFs) is addressed. It is assumed that the system parameters are unknown and the vehicle is underactuated. An adaptive controller is proposed, based on Lyapunov׳s direct method and the back-stepping technique, which interestingly guarantees robustness against parameter uncertainties. The desired trajectory can be any sufficiently smooth bounded curve parameterized by time even if consist of straight line. In contrast with the majority of research in this field, the likelihood of actuators׳ saturation is considered and another adaptive controller is designed to overcome this problem, in which control signals are bounded using saturation functions. The nonlinear adaptive control scheme yields asymptotic convergence of the vehicle to the reference trajectory, in the presence of parametric uncertainties. The stability of the presented control laws is proved in the sense of Lyapunov theory and Barbalat׳s lemma. Efficiency of presented controller using saturation functions is verified through comparing numerical simulations of both controllers.

Structuring of Indo-Pacific fish assemblages along the mangrove-seagrass continuum

Indo-Pacific mangrove swamps and seagrass beds are commonly located in close proximity to each other, often creating complex ecosystems linked by biological and physical processes. Although they are thought to provide important nursery habitats for fish, only limited information exists about their usage by fish outside of estuaries. The present study investigated fish assemblages in non-estuarine intertidal habitats where mangroves and seagrass overlap (the mangrove-seagrass continuum). Three habitats (mangrove, mangrove edge, seagrass) were sampled at 4 sites of the Wakatobi Marine National Park, Indonesia, using underwater visual census. Ninety-one species of fish were observed at a mean density of 130.1 +/- 37.2 ind. 1000 m(-2). Predatory fish (fish that feed on invertebrates and/or fish) were the most dominant feeding groups in the mangroves, whilst omnivores dominated on the mangrove edge and in the seagrass. Although the habitats along the mangrove-seagrass continuum were observed to be important for many fish, only 22 of the 942 coral reef species known within the area utilised mangroves as nursery habitat and only 15 utilised seagrass. Despite finding evidence that nursery grounds in mangroves and seagrass may not directly support high coral reef fish diversity, many of the coral reef nursery species found in this study are likely to be key herbivores or apex predators as adult fish on local coral reefs, and thus highly important to local fisheries. Although mangroves are not permanently inundated by the tide, this study highlights their importance as fish habitats, which at high tide support a greater abundance of fish than seagrass beds. In the light of the high rate of destruction of these habitats, their role in supporting fish assemblages requires consideration in marine resource management programs.

Seabed Biodiversity on the Continental Shelf of the Great Barrier Reef World Heritage Area

The Great Barrier Reef is a unique World Heritage Area of national and international significance. As a multiple use Marine Park, activities such as fishing and tourism occur along with conservation goals. Managers need information on habitats and biodiversity distribution and risks to ensure these activities are conducted sustainably. However, while the coral reefs have been relatively well studied, less was known about the deeper seabed in the region. From 2003 to 2006, the GBR Seabed Biodiversity Project has mapped habitats and their associated biodiversity across the length and breadth of the Marine Park to provide information that will help managers with conservation planning and to assess whether fisheries are ecologically sustainable, as required by environmental protection legislation (e.g. EPBC Act 1999). Holistic information on the biodiversity of the seabed was acquired by visiting almost 1,500 sites, representing a full range of known environments, during 10 month-long voyages on two vessels and deploying several types of devices such as: towed video and digital cameras, baited remote underwater video stations (BRUVS), a digital echo-sounder, an epibenthic sled and a research trawl to collect samples for more detailed data about plants, invertebrates and fishes on the seabed. Data were collected and processed from >600 km of towed video and almost 100,000 photos, 1150 BRUVS videos, ~140 GB of digital echograms, and from sorting and identification of ~14,000 benthic samples, ~4,000 seabed fish samples, and ~1,200 sediment samples.

A bottom-up integration of vision and actions to create cognitive humanoids

In recent years more and more complex humanoid robots have been developed. On the other hand programming these systems has become more difficult. There is a clear need for such robots to be able to adapt and perform certain tasks autonomously, or even learn by themselves how to act. An important issue to tackle is the closing of the sensorimotor loop. Especially when talking about humanoids the tight integration of perception with actions will allow for improved behaviours, embedding adaptation on the lower-level of the system.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Design and flight testing of a bio-inspired plume tracking algorithm for unmanned serial vehicles

There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).

MPC controlled multirotor with suspended slung load: System architecture and visual load detection

There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.

Stock assessment of the Queensland east coast common coral trout (Plectropomus leopardus) fishery

Common coral trout Plectropomus leopardus is an iconic fish of the Great Barrier Reef (GBR) and is the most important fish for the commercial fishery there. Most of the catch is exported live to Asia. This stock assessment was undertaken in response to falls in catch sizes and catch rates in recent years, in order to gauge the status of the stock. It is the first stock assessment ever conducted of coral trout on the GBR, and brings together a multitude of different data sources for the first time. The GBR is very large and was divided into a regional structure based on the Bioregions defined by expert committees appointed by the Great Barrier Reef Marine Park Authority (GBRMPA) as part of the 2004 rezoning of the GBR. The regional structure consists of six Regions, from the Far Northern Region in the north to the Swains and Capricorn–Bunker Regions in the south. Regions also closely follow the boundaries between Bioregions. Two of the northern Regions are split into Subregions on the basis of potential changes in fishing intensity between the Subregions; there are nine Subregions altogether, which include four Regions that are not split. Bioregions are split into Subbioregions along the Subregion boundaries. Finally, each Subbioregion is split into a “blue” population which is open to fishing and a “green” population which is closed to fishing. The fishery is unusual in that catch rates as an indicator of abundance of coral trout are heavily influenced by tropical cyclones. After a major cyclone, catch rates fall for two to three years, and rebound after that. This effect is well correlated with the times of occurrence of cyclones, and usually occurs in the same month that the cyclone strikes. However, statistical analyses correlating catch rates with cyclone wind energy did not provide significantly different catch rate trends. Alternative indicators of cyclone strength may explain more of the catch rate decline, and future work should investigate this. Another feature of catch rates is the phenomenon of social learning in coral trout populations, whereby when a population of coral trout is fished, individuals quickly learn not to take bait. Then the catch rate falls sharply even when the population size is still high. The social learning may take place by fish directly observing their fellows being hooked, or perhaps heeding a chemo-sensory cue emitted by fish that are hooked. As part of the assessment, analysis of data from replenishment closures of Boult Reef in the Capricorn–Bunker Region (closed 1983–86) and Bramble Reef in the Townsville Subregion (closed 1992–95) estimated a strong social learning effect. A major data source for the stock assessment was the large collection of underwater visual survey (UVS) data collected by divers who counted the coral trout that they sighted. This allowed estimation of the density of coral trout in the different Bioregions (expressed as a number of fish per hectare). Combined with mapping data of all the 3000 or so reefs making up the GBR, the UVS results provided direct estimates of the population size in each Subbioregion. A regional population dynamic model was developed to account for the intricacies of coral trout population dynamics and catch rates. Because the statistical analysis of catch rates did not attribute much of the decline to tropical cyclones, (and thereby implied “real” declines in biomass), and because in contrast the UVS data indicate relatively stable population sizes, model outputs were unduly influenced by the unlikely hypothesis that falling catch rates are real. The alternative hypothesis that UVS data are closer to the mark and declining catch rates are an artefact of spurious (e.g., cyclone impact) effects is much more probable. Judging by the population size estimates provided by the UVS data, there is no biological problem with the status of coral trout stocks. The estimate of the total number of Plectropomus leopardus on blue zones on the GBR in the mid-1980s (the time of the major UVS series) was 5.34 million legal-sized fish, or about 8400 t exploitable biomass, with an 2 additional 3350 t in green zones (using the current zoning which was introduced on 1 July 2004). For the offshore regions favoured by commercial fishers, the figure was about 4.90 million legal-sized fish in blue zones, or about 7700 t exploitable biomass. There is, however, an economic problem, as indicated by relatively low catch rates and anecdotal information provided by commercial fishers. The costs of fishing the GBR by hook and line (the only method compatible with the GBR’s high conservation status) are high, and commercial fishers are unable to operate profitably when catch rates are depressed (e.g., from a tropical cyclone). The economic problem is compounded by the effect of social learning in coral trout, whereby catch rates fall rapidly if fishers keep returning to the same fishing locations. In response, commercial fishers tend to spread out over the GBR, including the Far Northern and Swains Regions which are far from port and incur higher travel costs. The economic problem provides some logic to a reduction in the TACC. Such a reduction during good times, such as when the fishery is rebounding after a major tropical cyclone, could provide a net benefit to the fishery, as it would provide a margin of stock safety and make the fishery more economically robust by providing higher catch rates during subsequent periods of depressed catches. During hard times when catch rates are low (e.g., shortly after a major tropical cyclone), a change to the TACC would have little effect as even a reduced TACC would not come close to being filled. Quota adjustments based on catch rates should take account of long-term trends in order to mitigate variability and cyclone effects in data.

Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

A Distributed Robotic Vision Service

Robotic vision is limited by line of sight and onboard camera capabilities. Robots can acquire video or images from remote cameras, but processing additional data has a computational burden. This paper applies the Distributed Robotic Vision Service, DRVS, to robot path planning using data outside line-of-sight of the robot. DRVS implements a distributed visual object detection service to distributes the computation to remote camera nodes with processing capabilities. Robots request task-specific object detection from DRVS by specifying a geographic region of interest and object type. The remote camera nodes perform the visual processing and send the high-level object information to the robot. Additionally, DRVS relieves robots of sensor discovery by dynamically distributing object detection requests to remote camera nodes. Tested over two different indoor path planning tasks DRVS showed dramatic reduction in mobile robot compute load and wireless network utilization.

Find my office: Navigating real space from semantic descriptions

This paper shows that by using only symbolic language phrases, a mobile robot can purposefully navigate to specified rooms in previously unexplored environments. The robot intelligently organises a symbolic language description of the unseen environment and “imagines” a representative map, called the abstract map. The abstract map is an internal representation of the topological structure and spatial layout of symbolically defined locations. To perform goal-directed exploration, the abstract map creates a high-level semantic plan to reason about spaces beyond the robot’s known world. While completing the plan, the robot uses the metric guidance provided by a spatial layout, and grounded observations of door labels, to efficiently guide its navigation. The system is shown to complete exploration in unexplored spaces by travelling only 13.3% further than the optimal path.

The effects of eutrophication on alternative reproductive tactics in threespine sticklebacks

When organisms compete for mates and fertilisations, the process of sexual selection drives the evolution of traits that increase reproductive success. The traits targeted by selection, and the extent to which they change, are constrained by the local environment. Sexual selection due to female mate choice can be undermined by alternative reproductive tactics (ARTs), which refers to discontinuous variation in traits or behaviours used in reproduction. As human activities are rapidly changing our planet, this raises the question how ARTs will be affected. Fish show a bewildering diversity of ARTs, which make them good model organisms to answer these questions. One example of human-induced environmental change, which is affecting aquatic ecosystems around the world, is eutrophication, the over-enrichment of water bodies with nutrients. One of its effects is decreased underwater visibility due to increases in both turbidity and vegetation density. The aims of this thesis were to investigate the effects increased turbidity and vegetation density have on an ART in sticklebacks, a fish common to marine and fresh water bodies of the Northern hemisphere. I furthermore investigated how this affected sexual selection for male size, a trait commonly under selection. I used a combination of behavioural observations in microcosms, where I manipulated underwater visibility, with collection of genetic material to reconstruct parentage of broods, and thus identify sneak fertilisations. The results show that turbidity might have weak negative effects on the frequency of sneaking behaviour, although this behaviour was rather infrequent in these experiments, which complicates firm conclusions. In dense vegetation the number of sneak fertilisations decreased slightly, as fewer nesting males sneaked, while the number of non-nesting males sneaking remained constant. The paternity analyses revealed that a significantly smaller fraction of eggs was sneak fertilised under dense vegetation. Furthermore, amongst the nesting males that sneaked, the amount of eggs sneak fertilised correlated positively with courtship success. A reduction in sneaking by these males under dense vegetation equalised the distribution of fertilisation success, in turn contributing to a decrease in the opportunity for selection. Under dense vegetation significantly more males built nests, which has also been observed in previous field studies. In a separate experiment we addressed if such changes in the proportion of nesters and non-nesters, without changes in visibility, affected the incidence of sneak fertilisation. My results show this was not the case, likely because sneaking is an opportunistic tactic shown by both nesters and non-nesters. Non-nesters did sneak proportionately more when there were many of them, which could be due to changes in the cost-benefit ratio of sneaking. As nesters can only attack one intruder at a time, the costs and risks per sneaker will decrease as the number of sneakers increases. The defensive behaviours shown by the nesters before spawning shifted to a more aggressive form of nest defence. This could be because less aggressive behaviours lose their effectiveness when the number of intruders increases. It could also indicate that the risks associated with aggressive behaviours decrease when there are fewer fellow nesters, as other studies indicate nesters are competitive and aggressive individuals. Under turbid conditions I did not detect changes in the opportunity for selection, based on fertilisation success, nor was male size under significant selection under clear or turbid conditions. More thorough analyses under densely vegetated conditions across the nesting, courtship and fertilisation stages revealed a decrease in the opportunity for selection across all stages. A reduction in sneaking by nesters contributed to this. During the nesting stage, but not during later stages, body size was under significant directional selection under sparse, but not dense vegetation. This illustrates the importance of considering all selection stages to get a complete picture of how environmental changes affect sexual selection. Leaving out certain stages or subgroups can result in incomplete or misleading results.

Photobiological studies of Baltic Sea phytoplankton

Phytoplankton ecology and productivity is one of the main branches of contemporary oceanographic research. Research groups in this branch have increasingly started to utilise bio-optical applications. My main research objective was to critically investigate the advantages and deficiencies of the fast repetition rate (FRR) fluorometry for studies of productivity of phytoplankton, and the responses of phytoplankton towards varying environmental stress. Second, I aimed to clarify the applicability of the FRR system to the optical environment of the Baltic Sea. The FRR system offers a highly dynamic tool for studies of phytoplankton photophysiology and productivity both in the field and in a controlled environment. The FRR metrics obtain high-frequency in situ determinations of the light-acclimative and photosynthetic parameters of intact phytoplankton communities. The measurement protocol is relatively easy to use without phases requiring analytical determinations. The most notable application of the FRR system lies in its potential for making primary productivity (PP) estimations. However, the realisation of this scheme is not straightforward. The FRR-PP, based on the photosynthetic electron flow (PEF) rate, are linearly related to the photosynthetic gas exchange (fixation of 14C) PP only in environments where the photosynthesis is light-limited. If the light limitation is not present, as is usually the case in the near-surface layers of the water column, the two PP approaches will deviate. The prompt response of the PEF rate to the short-term variability in the natural light field makes the field comparisons between the PEF-PP and the 14C-PP difficult to interpret, because this variability is averaged out in the 14C-incubations. Furthermore, the FRR based PP models are tuned to closely follow the vertical pattern of the underwater irradiance. Due to the photoacclimational plasticity of phytoplankton, this easily leads to overestimates of water column PP, if precautionary measures are not taken. Natural phytoplankton is subject to broad-waveband light. Active non-spectral bio-optical instruments, like the FRR fluorometer, emit light in a relatively narrow waveband, which by its nature does not represent the in situ light field. Thus, the spectrally-dependent parameters provided by the FRR system need to be spectrally scaled to the natural light field of the Baltic Sea. In general, the requirement of spectral scaling in the water bodies under terrestrial impact concerns all light-adaptive parameters provided by any active non-spectral bio-optical technique. The FRR system can be adopted to studies of all phytoplankton that possess efficient light harvesting in the waveband matching the bluish FRR excitation. Although these taxa cover the large bulk of all the phytoplankton taxa, one exception with a pronounced ecological significance is found in the Baltic Sea. The FRR system cannot be used to monitor the photophysiology of the cyanobacterial taxa harvesting light in the yellow-red waveband. These taxa include the ecologically-significant bloom-forming cyanobacterial taxa in the Baltic Sea.