Learning Birds-Eye View Representations for Autonomous Driving

Over the past few years, progress towards the ambitious goal of widespread fully-autonomous vehicles on our roads has accelerated dramatically. This progress has been spurred largely by the success of highly accurate LiDAR sensors, as well the use of detailed high-resolution maps, which together allow a vehicle to navigate its surroundings effectively. Often, however, one or both of these resources may be unavailable, whether due to cost, sensor failure, or the need to operate in an unmapped environment. The aim of this thesis is therefore to demonstrate that it is possible to build detailed three-dimensional representations of traffic scenes using only 2D monocular camera images as input. Such an approach faces many challenges: most notably that 2D images do not provide explicit 3D structure. We overcome this limitation by applying a combination of deep learning and geometry to transform image-based features into an orthographic birds-eye view representation of the scene, allowing algorithms to reason in a metric, 3D space. This approach is applied to solving two challenging perception tasks central to autonomous driving. The first part of this thesis addresses the problem of monocular 3D object detection, which involves determining the size and location of all objects in the scene. Our solution was based on a novel convolutional network architecture that processed features in both the image and birds-eye view perspective. Results on the KITTI dataset showed that this network outperformed existing works at the time, and although more recent works have improved on these results, we conducted extensive analysis to find that our solution performed well in many difficult edge-case scenarios such as objects close to or distant from the camera. In the second part of the thesis, we consider the related problem of semantic map prediction. This consists of estimating a birds-eye view map of the world visible from a given camera, encoding both static elements of the scene such as pavement and road layout, as well as dynamic objects such as vehicles and pedestrians. This was accomplished using a second network that built on the experience from the previous work and achieved convincing performance on two real-world driving datasets. By formulating the maps as an occupancy grid map (a widely used representation from robotics), we were able to demonstrate how predictions could be accumulated across multiple frames, and that doing so further improved the robustness of maps produced by our system.Toyota Motors Europ

Multi-scale Rule-of-Mixtures Model of Carbon Nanotube/Carbon Fiber/Epoxy Lamina

A unidirectional carbon fiber/epoxy lamina in which the carbon fibers are coated with single-walled carbon nanotubes is modeled with a multi-scale method, the atomistically informed rule-of-mixtures. This multi-scale model is designed to include the effect of the carbon nanotubes on the constitutive properties of the lamina. It included concepts from the molecular dynamics/equivalent continuum methods, micromechanics, and the strength of materials. Within the model both the nanotube volume fraction and nanotube distribution were varied. It was found that for a lamina with 60% carbon fiber volume fraction, the Young's modulus in the fiber direction varied with changes in the nanotube distribution, from 138.8 to 140 GPa with nanotube volume fractions ranging from 0.0001 to 0.0125. The presence of nanotube near the surface of the carbon fiber is therefore expected to have a small, but positive, effect on the constitutive properties of the lamina

Development of mathematical pathways for VET students to articulate to related higher education courses: a focus on engineering

Australia needs more qualified professionals in the Science, Technology, Engineering, and Mathematics (STEM) areas. The national focus on widening participation in higher education (HE) includes strengthening pathways from vocational education and training (VET). VET students often lack the mathematics skills necessary to articulate successfully to their chosen university degrees. Current approaches such as bridging and foundation mathematics programs are not tailored or sufficiently contextualised for VET articulants. This project is developing a mathematics pathway designed to improve the readiness of VET engineering diploma graduates for higher education study in engineering degree programs. Arrangements are flexible so that students can complete these pathways either as part of their engineering diploma as a VET student or as part of preparatory study at the diploma level at university. Many VET students are granted credit when entering a HE course in engineering and can transfer directly to second year units which may assume a level of mathematical knowledge by the university. However, in the VET Diploma of Engineering Technical (MEM50212), there is only one core unit in mathematics (MEM30012A) equivalent to year 9 level and there are two mathematics electives, MEM23004A and MEM23007A, which are part of the advanced diploma and often not taught by many TAFE providers due to student demand and staff capabilities. The lack of required mathematics often leaves the student with a large gap in the required knowledge for success in HE. The project has been underway for over a year and significant progress has been made in developing the pathway for engineering. To date, the mathematical knowledge outcomes from the VET courses have been mapped to the requirements of the HE courses at the University of Tasmania, Flinders University and James Cook University. Gaps in mathematical knowledge have been identified. A formal articulation agreement has been established through TasTAFE and the University of Tasmania where current VET students will be able to enroll in the university foundation mathematics units and receive credit towards their VET diploma in engineering. In addition to the foundation units, the students need to do an online component. This consists of a few compulsory topics which are not covered in the foundation units with supporting examples, practice problems, practical application and self-assessed quizzes for each mathematics topic covered in the foundation units, contextualised to engineering. VET students are applied learners and therefore often struggle with the transition to HE. The online component of the pathway is designed to support the student by providing the context to the mathematics they are learning. Another advantage of the pathway is that it exposes the VET students to HE units and the university environment while satisfying the university mathematics entry requirements

Effect of thermal phase fluctuations on the superfluid density of two-dimensional superconducting films

High precision measurements of the complex sheet conductivity of superconducting Mo77Ge23 thin films have been made from 0.4 K through Tc. A sharp drop in the inverse sheet inductance, 1/L(T), is observed at a temperature, Tc, which lies below the mean-field transition temperature, Tco. Just below Tc, the suppression of 1/L(T) below its mean-field value indicates that longitudinal phase fluctuations have nearly their full classical amplitude, but they disappear rapidly as T decreases. We argue that there is a quantum crossover at about 0.94 Tco, below which classical phase fluctuations are suppressed.Comment: 14 pages, 3 figures. Subm. to PR

Gold(I) Fluorohalides: Theory and Experiment

The anionic trifluoromethylgold(I) derivatives [CF3AuX]−, which have been prepared and isolated as their [PPh4]+ salts in good yield, undergo thermally induced difluorocarbene extrusion in the gas phase, giving rise to the mixed gold(I) fluorohalide complexes [F−Au−X]− (X=Cl, Br, I). These triatomic species have been detected by tandem mass spectrometry (MS2) experiments and their properties have been analyzed by DFT methods. The CF2 extrusion mechanism from the Au−CF3 moiety serves as a model for the CF2 insertion into the Au−F bond, since both reactivity channels are connected by the microreversibility principle

Development of mathematical pathways for vet students to articulate to related higher education courses

Australia needs more qualified professionals in the areas of engineering, education, health and other sciences. The national focus on widening participation in higher education (HE) includes strengthening pathways from vocational education and training (VET). VET students often lack the mathematics skills necessary to articulate successfully to their chosen degrees. Current approaches such as bridging and foundation mathematics programs, and university in-degree support, are fragmented and not tailored or sufficiently contextualised for VET articulants. Flexible approaches are needed that enable institutions to assess the numeracy skills of VET articulants and provide resources and support to build their mathematical skills and confidence. This project is developing a series of mathematics pathways designed to improve the readiness of VET qualified students for higher education study in the areas of engineering, education and health science. Year 1 of this project focuses on engineering and education. The main VET qualifications and HE education courses have been identified and mapping the mathematical gap in knowledge between the two is underway. Mathematical pathways will be delivered as Open Education Resources and designed to be delivered flexibly. This presentation will review the progress on the mathematical pathway development and review the gaps that exist between the two sectors

Effect of Thermal Phase Fluctuations on the Inductances of Josephson Junctions, Arrays of Junctions, and Superconducting Films

We calculate the factor by which thermal phase fluctuations, as distinct from phase-slip fluctuations, increase the inductance, LJ, of a resistively-shunted Josephson junction (JJ) above its mean-field value, L0. We find that quantum mechanics suppresses fluctuations when T drops below a temperature, TQ = h/kBGL0, where G is the shunt conductance. Examination of the calculated sheet inductance, LA(T)/L0(T), of arrays of JJ's reveals that 2-D interconnections halve fluctuation effects, while reducing phase-slip effects by a much larger factor. Guided by these results, we calculate the sheet inductance, LF(T)/L0(T), of 2-D films by treating each plasma oscillation mode as an overdamped JJ. In disordered s-wave superconductors, quantum suppression is important for LF(0)/LF(T) > 0.14, (or, T/TC0 < 0.94). In optimally doped YBCO and BSCCO quantum suppression is important for l2(0)/l2(T) > 0.25, where l is the penetration depth.Comment: 15 pages; 4 figures. Submitted to Physical Review B, May 199

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)