Distribution of respiratory droplets in enclosed environments under different air distribution methods

Dispersion characteristics of respiratory droplets in indoor environments are of special interest in controlling transmission of airborne diseases. This study adopts an Eulerian method to investigate the spatial concentration distribution and temporal evolution of exhaled and sneezed/coughed droplets within the range of 1.0~10.0μm in an office room with three air distribution methods, i.e. mixing ventilation (MV), displacement ventilation (DV), and under-floor air distribution (UFAD). The diffusion, gravitational settling, and deposition mechanism of particulate matters are well accounted in the one-way coupling Eulerian approach. The simulation results find that exhaled droplets with diameters up to 10.0μm from normal respiration process are uniformly distributed in MV, while they are trapped in the breathing height by thermal stratifications in DV and UFAD, resulting in a high droplet concentration and a high exposure risk to other occupants. Sneezed/coughed droplets are diluted much slower in DV/UFAD than in MV. Low air speed in the breathing zone in DV/UFAD can lead to prolonged residence of droplets in the breathing zone.

Particle emission factors during cooking activities

Exposure to particles emitted by cooking activities may be responsible for a variety of respiratory health effects. However, the relationship between these exposures and their subsequent effects on health cannot be evaluated without understanding the properties of the emitted aerosol or the main parameters that influence particle emissions during cooking. Whilst traffic-related emissions, stack emissions and ultrafine particle concentrations (UFP, diameter < 100 nm) in urban ambient air have been widely investigated for many years, indoor exposure to UFPs is a relatively new field and in order to evaluate indoor UFP emissions accurately, it is vital to improve scientific understanding of the main parameters that influence particle number, surface area and mass emissions. The main purpose of this study was to characterise the particle emissions produced during grilling and frying as a function of the food, source, cooking temperature and type of oil. Emission factors, along with particle number concentrations and size distributions were determined in the size range 0.006-20 m using a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS). An infrared camera was used to measure the temperature field. Overall, increased emission factors were observed to be a function of increased cooking temperatures. Cooking fatty foods also produced higher particle emission factors than vegetables, mainly in terms of mass concentration, and particle emission factors also varied significantly according to the type of oil used.

Implication of global warming on air-conditioned office buildings in Australia

As climate change will entail new conditions for the built environment, the thermal behaviour of air-conditioned office buildings may also change. Using building computer simulations, the impact of warmer weather is evaluated on the design and performance of air-conditioned office buildings in Australia, including the increased cooling loads and probable indoor temperature increases due to a possibly undersized air-conditioning system, as well as the possible change in energy use. It is found that existing office buildings would generally be able to adapt to the increasing warmth of year 2030 Low and High scenarios projections and the year 2070 Low scenario projection. However, for the 2070 High scenario, the study indicates that the existing office buildings in all capital cities of Australia would suffer from overheating problems. For existing buildings designed for current climate conditions, it is shown that there is a nearly linear correlation between the increase of average external air temperature and the increase of building cooling load. For the new buildings designed for warmer scenarios, a 28-59% increase of cooling capacity under the 2070 High scenario would be required.

Polyfluoroalkyl chemicals in pooled blood serum from infants, children and adults in Australia

Polyfluoroalkyl chemicals (PFCs) have been used worldwide for more than 50 years in a wide variety of industrial and consumer products. Limited data exist on human exposure to PFCs in the Southern Hemisphere. Human blood serum collected in southeast Queensland, Australia, in 2006−2007 from 2420 donors was pooled according to age (cord blood, 0−0.5, 0.6−1, 1.1−1.5, 1.6−2, 2.1−2.5, 2.6−3, 3.1−3.5, 3.6−4, 4.1−6, 6.1−9, 9.1−12, 12.1−15, 16−30, 31−45, 46−60, and >60 years) and gender and was analyzed for eight PFCs. Across all pools, perfluorooctane sulfonate (PFOS) was detected at the highest mean concentration (15.2 ng/mL) followed by perfluorooctanoate (PFOA, 6.4 ng/mL), perfluorohexane sulfonate (PFHxS, 3.1 ng/mL), perfluorononanoate (PFNA, 0.8 ng/mL), 2-(N-methyl-perfluorooctance sulfonamide) acetate (Me-PFOSA-AcOH, 0.66 ng/mL), and perfluorodecanoate (PFDeA, 0.29 ng/mL). Perfluorooctane sulfonamide was detected in only 24% of the pools, and 2-(N-ethylperfluorooctane sulfonamide) acetate was detected in only one. PFOS concentrations were significantly higher in pools from adult males than from adult females (p = 0.002); no gender differences were apparent in the pools from children (<12 years old). The highest mean concentrations of PFOA, PFHxS, PFNA, PFDeA, and Me-PFOSA-AcOH were found in children <15 years, while PFOS was highest in adults >60 years. Investigation into the sources and exposure pathways in Australia, in particular for children, is necessary as well as continued biomonitoring to determine the potential effects on human concentrations as a result of changes in the PFC manufacturing practices, including the cessation of production of several PFCs.

Vision-based topological mapping and localisation

Competent navigation in an environment is a major requirement for an autonomous mobile robot to accomplish its mission. Nowadays, many successful systems for navigating a mobile robot use an internal map which represents the environment in a detailed geometric manner. However, building, maintaining and using such environment maps for navigation is difficult because of perceptual aliasing and measurement noise. Moreover, geometric maps require the processing of huge amounts of data which is computationally expensive. This thesis addresses the problem of vision-based topological mapping and localisation for mobile robot navigation. Topological maps are concise and graphical representations of environments that are scalable and amenable to symbolic manipulation. Thus, they are well-suited for basic robot navigation applications, and also provide a representational basis for the procedural and semantic information needed for higher-level robotic tasks. In order to make vision-based topological navigation suitable for inexpensive mobile robots for the mass market we propose to characterise key places of the environment based on their visual appearance through colour histograms. The approach for representing places using visual appearance is based on the fact that colour histograms change slowly as the field of vision sweeps the scene when a robot moves through an environment. Hence, a place represents a region of the environment rather than a single position. We demonstrate in experiments using an indoor data set, that a topological map in which places are characterised using visual appearance augmented with metric clues provides sufficient information to perform continuous metric localisation which is robust to the kidnapped robot problem. Many topological mapping methods build a topological map by clustering visual observations to places. However, due to perceptual aliasing observations from different places may be mapped to the same place representative in the topological map. A main contribution of this thesis is a novel approach for dealing with the perceptual aliasing problem in topological mapping. We propose to incorporate neighbourhood relations for disambiguating places which otherwise are indistinguishable. We present a constraint based stochastic local search method which integrates the approach for place disambiguation in order to induce a topological map. Experiments show that the proposed method is capable of mapping environments with a high degree of perceptual aliasing, and that a small map is found quickly. Moreover, the method of using neighbourhood information for place disambiguation is integrated into a framework for topological off-line simultaneous localisation and mapping which does not require an initial categorisation of visual observations. Experiments on an indoor data set demonstrate the suitability of our method to reliably localise the robot while building a topological map.

Experiments in outdoor operation of RatSLAM

This paper shows initial results in deploying the biologically inspired Simultaneous Localisation and Mapping system, RatSLAM, in an outdoor environment. RatSLAM has been widely tested in indoor environments on the task of producing topologically coherent maps based on a fusion of odometric and visual information. This paper details the changes required to deploy RatSLAM on a small tractor equipped with odometry and an omnidirectional camera. The principal changes relate to the vision system, with others required for RatSLAM to use omnidirectional visual data. The initial results from mapping around a 500 m loop are promising, with many improvements still to be made.

Simultaneous localisation and mapping from natural landmarks using RatSLAM

This paper describes the current state of RatSLAM, a Simultaneous Localisation and Mapping (SLAM) system based on models of the rodent hippocampus. RatSLAM uses a competitive attractor network to fuse visual and odometry information. Energy packets in the network represent pose hypotheses, which are updated by odometry and can be enhanced or inhibited by visual input. This paper shows the effectiveness of the system in real robot tests in unmodified indoor environments using a learning vision system. Results are shown for two test environments; a large corridor loop and the complete floor of an office building.

Experience mapping : producing spatially continuous environment representations using RatSLAM

RatSLAM is a system for vision-based Simultaneous Localisation and Mapping (SLAM) inspired by models of the rodent hippocampus. The system can produce stable representations of large complex environments during robot experiments in both indoor and outdoor environments. These representations are both topological and metric in nature, and can involve multiple representations of the same place as well as discontinuities. In this paper we describe a new technique known as experience mapping that can be used online with the RatSLAM system to produce world representations known as experience maps. These maps group together multiple place representations and are spatially continuous. A number of experiments have been conducted in simulation and a real world office environment. These experiments demonstrate the high degree to which experience maps are representative of the spatial arrangement of the environment.

Featureless vehicle-based visual SLAM with a consumer camera

The Simultaneous Localisation And Mapping (SLAM) problem is one of the major challenges in mobile robotics. Probabilistic techniques using high-end range finding devices are well established in the field, but recent work has investigated vision-only approaches. We present an alternative approach to the leading existing techniques, which extracts approximate rotational and translation velocity information from a vehicle-mounted consumer camera, without tracking landmarks. When coupled with an existing SLAM system, the vision module is able to map a 45 metre long indoor loop and a 1.6 km long outdoor road loop, without any parameter or system adjustment between tests. The work serves as a promising pilot study into ground-based vision-only SLAM, with minimal geometric interpretation of the environment.

Extending the dynamic range of robotic vision

Conventional cameras have limited dynamic range, and as a result vision-based robots cannot effectively view an environment made up of both sunny outdoor areas and darker indoor areas. This paper presents an approach to extend the effective dynamic range of a camera, achieved by changing the exposure level of the camera in real-time to form a sequence of images which collectively cover a wide range of radiance. Individual control algorithms for each image have been developed to maximize the viewable area across the sequence. Spatial discrepancies between images, caused by the moving robot, are improved by a real-time image registration process. The sequence is then combined by merging color and contour information. By integrating these techniques it becomes possible to operate a vision-based robot in wide radiance range scenes.

Modelling and control of a large quadrotor robot

Typical quadrotor aerial robots used in research weigh inlMMLBox and carry payloads measured in hundreds of grams. Several obstacles in design and control must be overcome to cater for expected industry demands that push the boundaries of existing quadrotor performance. The X-4 Flyer, a 4 kg quadrotor with a 1 kg payload, is intended to be prototypical of useful commercial quadrotors. The custom-built craft uses tuned plant dynamics with an onboard embedded attitude controller to stabilise flight. Independent linear SISO controllers were designed to regulate flyer attitude. The performance of the system is demonstrated in indoor and outdoor flight.

Field and Service Robotics Results of the 5th International Conference

The 5th International Conference on Field and Service Robotics (FSR05) was held in Port Douglas, Australia, on 29th - 31st July 2005, and brought together the worlds' leading experts in field and service automation. The goal of the conference was to report and encourage the latest research and practical results towards the use of field and service robotics in the community with particular focus on proven technology. The conference provided a forum for researchers, professionals and robot manufacturers to exchange up-to-date technical knowledge and experience. Field robots are robots which operate in outdoor, complex, and dynamic environments. Service robots are those that work closely with humans, with particular applications involving indoor and structured environments. There are a wide range of topics presented in this issue on field and service robots including: Agricultural and Forestry Robotics, Mining and Exploration Robots, Robots for Construction, Security & Defence Robots, Cleaning Robots, Autonomous Underwater Vehicles and Autonomous Flying Robots. This meeting was the fifth in the series and brings FSR back to Australia where it was first held. FSR has been held every 2 years, starting with Canberra 1997, followed by Pittsburgh 1999, Helsinki 2001 and Lake Yamanaka 2003.

Localization and navigation assisted by cooperating networked sensors and robots

In this paper we discuss how a network of sensors and robots can cooperate to solve important robotics problems such as localization and navigation. We use a robot to localize sensor nodes, and we then use these localized nodes to navigate robots and humans through the sensorized space. We explore these novel ideas with results from two large-scale sensor network and robot experiments involving 50 motes, two types of flying robot: an autonomous helicopter and a large indoor cable array robot, and a human-network interface. We present the distributed algorithms for localization, geographic routing, path definition and incremental navigation. We also describe how a human can be guided using a simple hand-held device that interfaces to this same environmental infrastructure.