Advantages of exploiting projection structure for segmenting dense 3D point clouds

Timely and comprehensive scene segmentation is often a critical step for many high level mobile robotic tasks. This paper examines a projected area based neighbourhood lookup approach with the motivation towards faster unsupervised segmentation of dense 3D point clouds. The proposed algorithm exploits the projection geometry of a depth camera to find nearest neighbours which is time independent of the input data size. Points near depth discontinuations are also detected to reinforce object boundaries in the clustering process. The search method presented is evaluated using both indoor and outdoor dense depth images and demonstrates significant improvements in speed and precision compared to the commonly used Fast library for approximate nearest neighbour (FLANN) [Muja and Lowe, 2009].

InsulLiving house post-occupancy energy performance report

This research was commissioned by Metecno Pty Ltd, trading as Bondor®. The InsulLiving house was designed and constructed by Bondor®. The house instrumentation (electricity circuits, indoor environment, weather station) was provided by Bondor and supplied and installed by independent contractors. This report contains analysis of data collected from the InsulLiving house at Burpengary during 1 year of occupancy by a family of four for the period 1 April 2012 – 31 March 2013. The data shows a daily average electricity consumption 48% less than the regional average. The analysis confirms that the 9 star house performed thermally slightly better than the simulated performance. The home was 'near zero energy', with its modest 2.1kW solar power system meeting all of the needs for space heating and cooling, lighting and most water heating.

Informational constraints on performance of dynamic interceptive actions

Utilising quantitative and qualitative research methods the thesis explored how movement patterns were coordinated under different conditions in elite athletes. Results revealed each elite athlete's ability to use multiple, varied information sources to guide successful task performance, highlighting the specific role of surrounding objects in the performance environment to perceptually guide behaviour. Combining elite coaching knowledge with empirical research enhanced understanding of the role of vision in regulating interceptive behaviours, enhancing the representative design of training environments. The main findings have been applied to training design of the Athletics Australia National Jumps Centre at the Queensland Academy of Sport in preparation for the World Indoor Championships, World Championships, and Olympic Games for Australian long and triple jumpers.

Resilient Navigation through Probabilistic Modality Reconfiguration

This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robot’s ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMP- based platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation fault.

Hybrid multi-channel cooperative spectrum sensing to satisfy channel target

Spectrum sensing of multiple primary user channels is a crucial function in cognitive radio networks. In this paper we propose an optimal, sensing resource allocation algorithm for multi-channel cooperative spectrum sensing. The channel target is implemented as an objective and constraint to ensure a pre-determined number of empty channels are detected for secondary user network operations. Based on primary user traffic parameters, we calculate the minimum number of primary user channels that must be sensed to satisfy the channel target. We implement a hybrid sensing structure by grouping secondary user nodes into clusters and assign each cluster to sense a different primary user channels. We then solve the resource allocation problem to find the optimal sensing configuration and node allocation to minimise sensing duration. Simulation results show that the proposed algorithm requires the shortest sensing duration to achieve the channel target compared to existing studies that require long sensing and cannot guarantee the target.

Rodent Scope: A User-Configurable Digital Wireless Telemetry System for Freely Behaving Animals

This paper describes the design and implementation of a wireless neural telemetry system that enables new experimental paradigms, such as neural recordings during rodent navigation in large outdoor environments. RoSco, short for Rodent Scope, is a small lightweight user-configurable module suitable for digital wireless recording from freely behaving small animals. Due to the digital transmission technology, RoSco has advantages over most other wireless modules of noise immunity and online user-configurable settings. RoSco digitally transmits entire neural waveforms for 14 of 16 channels at 20 kHz with 8-bit encoding which are streamed to the PC as standard USB audio packets. Up to 31 RoSco wireless modules can coexist in the same environment on non-overlapping independent channels. The design has spatial diversity reception via two antennas, which makes wireless communication resilient to fading and obstacles. In comparison with most existing wireless systems, this system has online user-selectable independent gain control of each channel in 8 factors from 500 to 32,000 times, two selectable ground references from a subset of channels, selectable channel grounding to disable noisy electrodes, and selectable bandwidth suitable for action potentials (300 Hz–3 kHz) and low frequency field potentials (4 Hz–3 kHz). Indoor and outdoor recordings taken from freely behaving rodents are shown to be comparable to a commercial wired system in sorting for neural populations. The module has low input referred noise, battery life of 1.5 hours and transmission losses of 0.1% up to a range of 10 m.

Assessing exposure to polybrominated diphenyl ethers (PBDEs) for workers in the vicinity of a large recycling facility

Increased levels of polybrominated diphenyl ethers (PBDEs) can occur particularly in dust and soil surrounding facilities that recycle products containing PBDEs. This may be the source of increased exposure for nearby workers and residents. To investigate, we measured PBDE levels in soil, office dust and blood of workers at the closest workplace (i.e. within 100m) to a large automotive shredding and metal recycling facility in Brisbane, Australia. The workplace investigated in this study was independent of the automotive shredding facility and was one of approximately 50 businesses of varying types within a relatively large commercial/industrial area surrounding the recycling facility. Concentrations of PBDEs in soils were at least an order of magnitude greater than background levels in the area. Congener profiles were dominated by larger molecular weight congeners; in particular BDE-209. This reflected the profile in outdoor air samples previously collected at this site. Biomonitoring data from blood serum indicated no differential exposure for workers near the recycling facility compared to a reference group of office workers, also in Brisbane. Unlike air, indoor dust and soil sample profiles, serum samples from both worker groups were dominated by congeners BDE-47, BDE-153, BDE-99, BDE-100 and BDE-183 and was similar to the profile previously reported in the general Australian population. Estimated exposures for workers near the industrial point source suggested indoor workers had significantly higher exposure than outdoor workers due to their exposure to indoor dust rather than soil. However, no relationship was observed between blood PBDE levels and different roles and activity patterns of workers on-site. These comparisons of PBDE levels in serum provide additional insight into the inter-individual variability within Australia. Results also indicate congener patterns in the workplace environment did not match blood profiles of workers. This was attributed to the relatively high background exposures for the general Australian population via dietary intake and the home environment.

An efficient and effective localization method for networked disjoint top-view cameras

Disjoint top-view networked cameras are among the most commonly utilized networks in many applications. One of the open questions for these cameras' study is the computation of extrinsic parameters (positions and orientations), named extrinsic calibration or localization of cameras. Current approaches either rely on strict assumptions of the object motion for accurate results or fail to provide results of high accuracy without the requirement of the object motion. To address these shortcomings, we present a location-constrained maximum a posteriori (LMAP) approach by applying known locations in the surveillance area, some of which would be passed by the object opportunistically. The LMAP approach formulates the problem as a joint inference of the extrinsic parameters and object trajectory based on the cameras' observations and the known locations. In addition, a new task-oriented evaluation metric, named MABR (the Maximum value of All image points' Back-projected localization errors' L2 norms Relative to the area of field of view), is presented to assess the quality of the calibration results in an indoor object tracking context. Finally, results herein demonstrate the superior performance of the proposed method over the state-of-the-art algorithm based on the presented MABR and classical evaluation metric in simulations and real experiments.

The Performance Nexus - A framework for improving energy efficiency in existing commercial buildings by considering a whole-of-building approach

Efforts to reduce carbon emissions in the buildings sector have been focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants,i something with much greater economic returns than energy savings. Reducing energy demand in green commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This paper outlines an investigation into these factors and focuses on better understanding the performance of and interaction between: design elements, internal environmental quality, occupant experience, tenant/leasing agreements, and building regulation and management. In doing so the paper presents a framework for improving energy efficiency in existing commercial buildings by considering a range of interconnected and synergistic elements.

The development of a simple multi-nodal tool to identify performance issues in existing commercial buildings

Australia’s building stock includes many older commercial buildings with numerous factors that impact energy performance and indoor environment quality. The built environment industry has generally focused heavily on improving physical building design elements for greater energy efficiency (such as retrofits and environmental upgrades), however there are noticeable ‘upper limits’ to performance improvements in these areas. To achieve a stepchange improvement in building performance, the authors propose that additional components need to be addressed in a whole of building approach, including the way building design elements are managed and the level of stakeholder engagement between owners, tenants and building managers. This paper focuses on the opportunities provided by this whole-of-building approach, presenting the findings of a research project undertaken through the Sustainable Built Environment National Research Centre (SBEnrc) in Australia. Researchers worked with a number of industry partners over two years to investigate issues facing stakeholders at base building and tenancy levels, and the barriers to improving building performance. Through a mixed-method, industry-led research approach, five ‘nodes’ were identified in whole-of-building performance evaluation, each with interlinking and overlapping complexities that can influence performance. The nodes cover building management, occupant experience, indoor environment quality, agreements and culture, and design elements. This paper outlines the development and testing of these nodes and their interactions, and the resultant multi-nodal tool, called the ‘Performance Nexus’ tool. The tool is intended to be of most benefit in evaluating opportunities for performance improvement in the vast number of existing low-performing building stock.

Greening Buildings : How can the performance of existing commercial buildings be improved?

Efforts to improve the performance of commercial buildings have often focused on encouraging green design, construction and building operation; however, the business case is not very compelling if considering the energy cost savings alone. In recent years green building has been driven by a sense that it will improve the productivity of occupants, something with even greater economic returns than energy savings. Reducing energy demand in commercial buildings in a way that encourages greater productivity is not yet well understood as it involves a set of complex and interdependent factors. This project investigates these factors and focuses on the performance of and interaction between: green design elements, indoor environment quality, tenant/ leasing agreements and culture, occupant experience, and building management practices.

A bayesian approach for place recognition

This paper presents a robust place recognition algorithm for mobile robots that can be used for planning and navigation tasks. The proposed framework combines nonlinear dimensionality reduction, nonlinear regression under noise, and Bayesian learning to create consistent probabilistic representations of places from images. These generative models are incrementally learnt from very small training sets and used for multi-class place recognition. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions, blurring and moving objects. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images, respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

Investigation of air quality at Lithgow Correctional Centre

This project was conducted at Lithgow Correctional Centre (LCC), NSW, Australia. Air quality field measurements were conducted on two occasions (23-27 May 2012, and 3-8 December 2012), just before and six months after the introduction of smoke free buildings policies (28 May 2012) at the LCC, respectively. The main aims of this project were to: (1) investigate the indoor air quality; (2) quantify the level of exposure to environmental tobacco smoke (ETS); (3) identify the main indoor particle sources; (4) distinguish between PM2.5 / particle number from ETS, as opposed to other sources; and (5) provide recommendations for improving indoor air quality and/or minimising exposure at the LCC. The measurements were conducted in Unit 5.2A, Unit 5.2B, Unit 1.1 and Unit 3.1, together with personal exposure measurements, based on the following parameters: -Indoor and outdoor particle number (PN) concentration in the size range 0.005-3 µm -Indoor and outdoor PM2.5 particle mass concentration -Indoor and outdoor VOC concentrations -Personal particle number exposure levels (in the size range 0.01-0.3 µm) -Indoor and outdoor CO and CO2 concentrations, temperature and relative humidity In order to enhance the outcomes of this project, the indoor and outdoor particle number (PN) concentrations were measured by two additional instruments (CPC 3787) which were not listed in the original proposal.

Exposure to ambient heat and urolithiasis among outdoor workers in Guangzhou, China

Objectives: To assess the impact of exposure to ambient heat on urolithiasis among outdoor workers in a subtropical city of China. Methods: The 2003–2010 health check data of a shipbuilding company in Guangzhou, China were acquired. 190 cases and 760 matched controls were involved in this study. We assessed the relationship between exposure to ambient heat and urolithiasis for different occupations using conditional logistic regression. Results: Spray painters were most likely to develop urolithiasis (OR = 4.4; 95% CI: 1.7, 11.4), followed by smelter workers (OR = 4.0; 95% CI: 1.8, 9.2), welders (OR = 3.7; 95% CI: 1.9, 7.2), production security and quality inspectors (OR = 2.7; 95% CI: 1.4, 3.0), and assemblers (OR = 2.2; 95% CI: 1.1, 4.3). Overall, outdoor workers were more likely to present with urolithiasis compared with indoor employees (p b 0.05). In addition, workers with longer cumulative exposure time (OR = 1.5; 95% CI: 1.2, 1.8) and abnormal blood pressure (OR = 1.6; 95% CI: 1.0, 2.5) had higher risk for urolithiasis. Conclusions: Our findings demonstrate a significant association between exposure to ambient heat and urolithiasis among outdoor working populations. Public health intervention strategies should be developed to specifically target outdoor occupations.

Joint 2D and 3D cues for image segmentation towards robotic applications

This thesis investigates the fusion of 3D visual information with 2D image cues to provide 3D semantic maps of large-scale environments in which a robot traverses for robotic applications. A major theme of this thesis was to exploit the availability of 3D information acquired from robot sensors to improve upon 2D object classification alone. The proposed methods have been evaluated on several indoor and outdoor datasets collected from mobile robotic platforms including a quadcopter and ground vehicle covering several kilometres of urban roads.