Robust sensing for a 3,500 tonne field robot

The mining industry is highly suitable for the application of robotics and automation technology since the work is arduous, dangerous and often repetitive. This paper discusses a robust sensing system developed to find and trade the position of the hoist ropes of a dragline. Draglines are large `walking cranes' used in open-pit coal mining to remove the material covering the coal seam. The rope sensing system developed uses two time-of-flight laser scanners. The finding algorithm uses a novel data association and tracking strategy based on pairing rope data.

Acoustic sensing: Roles and applications in monitoring avian biodiversity

This thesis examined the use of acoustic sensors for monitoring avian biodiversity. Acoustic sensors have the potential to significantly increase the spatial and temporal scale of ecological observations, however acoustic recordings of the environment can be opaque and complex. This thesis developed methods for analysing large volumes of acoustic data to maximise the detection of bird species, and compared the results of acoustic sensor biodiversity surveys with traditional bird survey techniques.

Anodized nanoporous WO3 Schottky contact structure for hydrogen and ethanol sensing

This paper reports the development of nanoporous tungsten trioxide (WO3) Schottky diode-based gas sensors. Nanoporous WO3 films were prepared by anodic oxidation of tungsten foil in ethylene glycol mixed with ammonium fluoride and a small amount of water. Anodization resulted in highly ordered WO3 films with a large surface-to-volume ratio. Utilizing these nanoporous structures, Schottky diode-based gas sensors were developed by depositing a platinum (Pt) catalytic contact and tested towards hydrogen gas and ethanol vapour. Analysis of the current–voltage characteristics and dynamic responses of the sensors indicated that these devices exhibited a larger voltage shift in the presence of hydrogen gas compared to ethanol vapour at an optimum operating temperature of 200 °C. The gas sensing mechanism was discussed, associating the response to the intercalating H+ species that are generated as a result of hydrogen and ethanol molecule breakdowns onto the Pt/WO3 contact and their spill over into nanoporous WO3.

Non-parametric consistency test for multiple-sensing-modality data fusion

Fusing data from multiple sensing modalities, e.g. laser and radar, is a promising approach to achieve resilient perception in challenging environmental conditions. However, this may lead to \emph{catastrophic fusion} in the presence of inconsistent data, i.e. when the sensors do not detect the same target due to distinct attenuation properties. It is often difficult to discriminate consistent from inconsistent data across sensing modalities using local spatial information alone. In this paper we present a novel consistency test based on the log marginal likelihood of a Gaussian process model that evaluates data from range sensors in a relative manner. A new data point is deemed to be consistent if the model statistically improves as a result of its fusion. This approach avoids the need for absolute spatial distance threshold parameters as required by previous work. We report results from object reconstruction with both synthetic and experimental data that demonstrate an improvement in reconstruction quality, particularly in cases where data points are inconsistent yet spatially proximal.

Towards the development of a low cost airborne sensing system to monitor dust particles after blasting at open-pit mine sites

Blasting is an integral part of large-scale open cut mining that often occurs in close proximity to population centers and often results in the emission of particulate material and gases potentially hazardous to health. Current air quality monitoring methods rely on limited numbers of fixed sampling locations to validate a complex fluid environment and collect sufficient data to confirm model effectiveness. This paper describes the development of a methodology to address the need of a more precise approach that is capable of characterizing blasting plumes in near-real time. The integration of the system required the modification and integration of an opto-electrical dust sensor, SHARP GP2Y10, into a small fixed-wing and multi-rotor copter, resulting in the collection of data streamed during flight. The paper also describes the calibration of the optical sensor with an industry grade dust-monitoring device, Dusttrak 8520, demonstrating a high correlation between them, with correlation coefficients (R2) greater than 0.9. The laboratory and field tests demonstrate the feasibility of coupling the sensor with the UAVs. However, further work must be done in the areas of sensor selection and calibration as well as flight planning.

A dynamic navigation model for unmanned aircraft systems and an application to autonomous front-on environmental sensing and photography using low-cost sensor systems

This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.

Conversion of n-type CuTCNQ into p-type nitrogen-doped CuO and the implication for room temperature gas sensing

Sensors to detect toxic and harmful gases are usually based on metal oxides that are operated at elevated temperature. However, enabling gas detection at room temperature (RT) is a significant ongoing challenge. Here, we address this issue by demonstrating that microrods of semiconducting CuTCNQ (TCNQ=7,7,8,8-tetracyanoquinodimethane) with nanostructured features can be employed as conductometric gas sensors operating at 50°C for detection of oxidizing and reducing gases such as NO2 and NH3. The sensor is evaluated at RT and up to 200°C. It was found that CuTCNQ is transformed into a N-doped CuO material with p-type conductivity when annealed at the maximum temperature. This is the first time that such a transformation, from a semiconducting charge transfer material into a N-doped metal oxide is detected. It is shown here that both the surface chemistry and the type of majority charge carrier within the sensing layer is critically important for the type of response towards oxidizing and reducing gases. A detailed physical description of NO2 and NH3 sensing mechanism at CuTCNQ and N-doped CuO is provided to explain the difference in the response. For the N-doped CuO sensor, a detection limit of 1 ppm for NO2 and 10 ppm for NH3 are achieved.

Design of redox/radical sensing molecules via Nitrile Imine-Mediated Tetrazole-ene Cycloaddition (NITEC)

The current study introduces a novel synthetic avenue for the preparation of profluorescent nitroxides via nitrile imine-mediated tetrazole-ene cycloaddition (NITEC). The photoinduced cycloaddition was performed under metal-free, mild conditions allowing the preparation of a library of the nitroxide functionalized pyrazolines and corresponding methoxyamines. High reaction rates and full conversion were observed, with the presence of the nitroxide having no significant impact on the cycloaddition performance. The formed products were investigated with respect to their photophysical properties in order to quantify their “switch on/off” behavior. The fluorescence quenching performance is strongly dependent on the distance between the chromophore and the free radical spin as demonstrated theoretically and experimentally. Highest levels of fluorescence quenching were achieved for pyrazolines with the nitroxide directly fused to the chromophore. Importantly, the pyrazoline profluorescent nitroxides were shown to efficiently act as sensors for redox/radical processes.

Collaborative data exploration interfaces - From participatory sensing to participatory sensemaking

As technological capabilities for capturing, aggregating, and processing large quantities of data continue to improve, the question becomes how to effectively utilise these resources. Whenever automatic methods fail, it is necessary to rely on human background knowledge, intuition, and deliberation. This creates demand for data exploration interfaces that support the analytical process, allowing users to absorb and derive knowledge from data. Such interfaces have historically been designed for experts. However, existing research has shown promise in involving a broader range of users that act as citizen scientists, placing high demands in terms of usability. Visualisation is one of the most effective analytical tools for humans to process abstract information. Our research focuses on the development of interfaces to support collaborative, community-led inquiry into data, which we refer to as Participatory Data Analytics. The development of data exploration interfaces to support independent investigations by local communities around topics of their interest presents a unique set of challenges, which we discuss in this paper. We present our preliminary work towards suitable high-level abstractions and interaction concepts to allow users to construct and tailor visualisations to their own needs.

Remote Sensing and Data Collection from Solar Powered Wireless Sensor Network using an Unmanned Aerial Vehicle System

Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Green Falcon and Raptor UAV for remote gas sensing

This report documents showcases my learning experiences and design of Green Falcon Solar Powered UAV. Only responsible aspects will be discussed inside this report. Using solar power that is captured by solar panels it can fly all day and also store power for night flying. Its major advantage lies in the fact that it is simple and versatile, which makes it applicable to a large range of UAVs of different wingspans. Green Falcon UAV is designed as a supporting tool for scientists to get a deeper understanding of gases exchange amongst ground plane and atmosphere

Affective sensing + wearable imaging: Vision impairment and implications for spatial enquiry

Recent interest in affect and the body have mobilized a contemporary review of aesthetics and phenomenology within architecture to unpack how environments affect spatial experience. Emerging spatial studies within the neuro-sciences, and their implications for architectural research as raised by architectural theorists Juhani Pallasmaa (2014) and Harry Mallgrave (2013) has been well supported by a raft of scientists and institutions including the prestigious Salk Institute. Although there has been some headway in spatial studies of the vision impaired (Cattaneo et al, 2011) to understand the role of their non-visual systems in assisting navigation and location, little is discussed in terms of their other abilities in sensing particular qualities of space which impinge upon emotion. This paper reviews a collection of studies exploring face vision and echo-location, amongst others, which provide insight into what might be termed affective perception of the vision impaired, and how further interplay between this research and the architectural field can contribute new knowledge regarding space and affect. By engaging with themes from the Aesthetics, Phenomenology and indeed Neuro-science fields, the paper provides background of current and potential cross disciplinary research, and highlights the role wearable technologies can play in enhancing knowledge of affective spatial experience.

Design and Simulation of a Solar Powered UAV for Remote Sensing Tasks Technical Report

This research deals with the development of a Solar-Powered UAV designed for remote sensing, in particular to the development of the autopilot sub-system and path planning. The design of the Solar-Powered UAS followed a systems engineering methodology, by first defining system architecture, and selecting each subsystem. Validation tests and integration of autopilot is performed, in order to evaluate the performances of each subsystem and to obtain a global operational system for data collection missions. The flight tests planning and simulation results are also explored in order to verify the mission capabilities using an autopilot on a UAS. The important aspect of this research is to develop a Solar-Powered UAS for the purpose of data collection and video monitoring, especially data and images from the ground; transmit to the GS (Ground Station), segment the collected data, and afterwards analyze it with a Matlab code.

Room temperature gas sensing properties of ultrathin carbon nanotubes by surfactant-free dip coating

Large-scale production of reliable carbon nanotubes (CNTs) based gas sensors involves the development of scalable and reliable processes for the fabrication of films with controlled morphology. Here, we report for the first time on highly scalable, ultrathin CNT films, to be employed as conductometric sensors for NO2 and NH3 detection at room temperature. The sensing films are produced by dip coating using dissolved CNTs in chlorosulfonic acid as a working solution. This surfactant-free approach does not require any post-treatment for the removal of dispersants or any CNTs functionalization, thus promising high quality CNTs for better sensitivity and low production costs. The effect of CNT film thickness and defect density on the gas sensing properties has been investigated. Detection limits of 1 ppm for NO2 and 7 ppm for NH3 have been achieved at room temperature. The experimental results reveal that defect density and film thickness can be controlled to optimize the sensing response. Gas desorption has been accelerated by continuous in-situ UV irradiation.