Improved measurement of depth perception

Electromechanical system for Howard-Dolman device was developed. System is used for human depth perception measurements without tactual stimuli

Study of filtration mechanics and sampling techniques Annual technical summary report, phase 4, 1967-1968

Filtration mechanics and fluid contamination control in hydraulic system

Study of filtration mechanics and sampling techniques, phase 4 Annual report, 1967-1968

Filtration mechanics and fluid contaminatio

Study of fluid transients in closed conduits annual report no. 1

Atmospheric density effect on computation of earth satellite orbit

Stochastic Path Planning for Autonomous Underwater Gliders with Safety Constraints

© 2019 IEEE. Autonomous underwater gliders frequently execute extensive missions with high levels of uncertainty due to limitations of sensing, control and oceanic forecasting. Glider path planning seeks an optimal path with respect to conflicting objectives, such as travel cost and safety, that must be explicitly balanced subject to these uncertainties. In this paper, we derive a set of recursive equations for state probability and expected travel cost conditional on safety, and use them to implement a new stochastic variant of FMT-{ast } in the context of two types of objective functions that allow a glider to reach a destination region with minimum cost or maximum probability of arrival given a safety threshold. We demonstrate the framework using three simulated examples that illustrate how user-prescribed safety constraints affect the results

Multi-robot region-of-interest reconstruction with Dec-MCTS

© 2019 IEEE. We consider the problem of reconstructing regions of interest of a scene using multiple robot arms and RGB-D sensors. This problem is motivated by a variety of applications, such as precision agriculture and infrastructure inspection. A viewpoint evaluation function is presented that exploits predicted observations and the geometry of the scene. A recently proposed non-myopic planning algorithm, Decentralised Monte Carlo tree search, is used to coordinate the actions of the robot arms. Motion planning is performed over a navigation graph that considers the high-dimensional configuration space of the robot arms. Extensive simulated experiments are carried out using real sensor data and then validated on hardware with two robot arms. Our proposed targeted information gain planner is compared to state-of-the-art baselines and outperforms them in every measured metric. The robots quickly observe and accurately detect fruit in a trellis structure, demonstrating the viability of the approach for real-world applications

Energy-optimal kinodynamic planning for underwater gliders in flow fields

We consider energy-optimal navigation planning in ow fields, which is a long-standing optimisation problem with no known analytical solution. Using the motivating example of an underwater glider subject to ocean currents, we present an asymptotically optimal planning framework that considers realistic vehicle dynamics and provably returns an optimal solution in the limit. One key idea that we introduce is to reformulate the dynamic control problem as a kinematic problem with trim states, which encapsulate the dynamics over suitably long distances. We report simulation examples that, surprisingly, contravene the use of regular 'sawtooth' paths currently in widespread use. We show that, when internal control mechanics are taken into account, energy-efficient paths do not necessarily follow a regular up-and-down pattern. Our work represents a principled planning framework for underwater gliders that will enable improved navigation capability for both commercial and defence applications

Active perception for plume source localisation with underwater gliders

© 2018 Australasian Robotics and Automation Association. All rights reserved. We consider the problem of localising an unknown underwater plume source in an energy-optimal manner. We first develop a specialised Gaussian process (GP) regression technique for estimating the source location given concentration measurements and an ambient flow field. Then, we use the GP upper confidence bound (GP-UCB) for active perception to choose sampling locations that both improve the estimate of the source and lead the glider to the correct source location. A trim-based FMT∗planner is then used to find the sequence of controls that minimise the energy consumption. We provide a theoretical guarantee on the performance of the algorithm, and demonstrate the algorithm using both artificial and experimental datasets

Evolutionary History and Attenuation of Myxoma Virus on Two Continents

The attenuation of myxoma virus (MYXV) following its introduction as a biological control into the European rabbit populations of Australia and Europe is the canonical study of the evolution of virulence. However, the evolutionary genetics of this profound change in host-pathogen relationship is unknown. We describe the genome-scale evolution of MYXV covering a range of virulence grades sampled over 49 years from the parallel Australian and European epidemics, including the high-virulence progenitor strains released in the early 1950s. MYXV evolved rapidly over the sampling period, exhibiting one of the highest nucleotide substitution rates ever reported for a double-stranded DNA virus, and indicative of a relatively high mutation rate and/or a continually changing selective environment. Our comparative sequence data reveal that changes in virulence involved multiple genes, likely losses of gene function due to insertion-deletion events, and no mutations common to specific virulence grades. Hence, despite the similarity in selection pressures there are multiple genetic routes to attain either highly virulent or attenuated phenotypes in MYXV, resulting in convergence for phenotype but not genotype. © 2012 Kerr et al

Online estimation of ocean current from sparse GPS data for underwater vehicles

© 2019 IEEE. Underwater robots are subject to position drift due to the effect of ocean currents and the lack of accurate localisation while submerged. We are interested in exploiting such position drift to estimate the ocean current in the surrounding area, thereby assisting navigation and planning. We present a Gaussian process (GP)-based expectation-maximisation (EM) algorithm that estimates the underlying ocean current using sparse GPS data obtained on the surface and dead-reckoned position estimates. We first develop a specialised GP regression scheme that exploits the incompressibility of ocean currents to counteract the underdetermined nature of the problem. We then use the proposed regression scheme in an EM algorithm that estimates the best-fitting ocean current in between each GPS fix. The proposed algorithm is validated in simulation and on a real dataset, and is shown to be capable of reconstructing the underlying ocean current field. We expect to use this algorithm to close the loop between planning and estimation for underwater navigation in unknown ocean currents