Aerial object following using visual fuzzy servoing

This article presents a visual servoing system to follow a 3D moving object by a Micro Unmanned Aerial Vehicle (MUAV). The presented control strategy is based only on the visual information given by an adaptive tracking method based on the colour information. A visual fuzzy system has been developed for servoing the camera situated on a rotary wing MAUV, that also considers its own dynamics. This system is focused on continuously following of an aerial moving target object, maintaining it with a fixed safe distance and centred on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation

A multi-resolution image alignment technique based on direct methods for pose estimation of aerial vehicles

In this paper, we seek to expand the use of direct methods in real-time applications by proposing a vision-based strategy for pose estimation of aerial vehicles. The vast majority of approaches make use of features to estimate motion. Conversely, the strategy we propose is based on a MR (Multi- Resolution) implementation of an image registration technique (Inverse Compositional Image Alignment ICIA) using direct methods. An on-board camera in a downwards-looking configuration, and the assumption of planar scenes, are the bases of the algorithm. The motion between frames (rotation and translation) is recovered by decomposing the frame-to-frame homography obtained by the ICIA algorithm applied to a patch that covers around the 80% of the image. When the visual estimation is required (e.g. GPS drop-out), this motion is integrated with the previous known estimation of the vehicles’ state, obtained from the on-board sensors (GPS/IMU), and the subsequent estimations are based only on the vision-based motion estimations. The proposed strategy is tested with real flight data in representative stages of a flight: cruise, landing, and take-off, being two of those stages considered critical: take-off and landing. The performance of the pose estimation strategy is analyzed by comparing it with the GPS/IMU estimations. Results show correlation between the visual estimation obtained with the MR-ICIA and the GPS/IMU data, that demonstrate that the visual estimation can be used to provide a good approximation of the vehicle’s state when it is required (e.g. GPS drop-outs). In terms of performance, the proposed strategy is able to maintain an estimation of the vehicle’s state for more than one minute, at real-time frame rates based, only on visual information.

Performance load testing and structural adequacy evaluation of road bridge decks

Many ageing road bridges, particularly timber bridges, require urgent improvement due to the demand imposed by the recent version of the Australian bridge loading code, AS 5100. As traffic volume plays a key role in the decision of budget allocations for bridge refurbishment/ replacement, many bridges in low volume traffic network remain in poor condition with axle load and/ or speed restrictions, thus disadvantaging many rural communities. This thesis examines an economical and environmentally sensible option of incorporating disused flat rail wagons (FRW) in the construction of bridges in low volume, high axle load road network. The constructability, economy and structural adequacy of the FRW road bridge is reported in the thesis with particular focus of a demonstration bridge commissioned in regional Queensland. The demonstration bridge comprises of a reinforced concrete slab (RCS) pavement resting on two FRWs with custom designed connection brackets at regular intervals along the span of the bridge. The FRW-RC bridge deck assembly is supported on elastomeric rubber pads resting on the abutment. As this type of bridge replacement technology is new and its structural design is not covered in the design standards, the in-service structural performance of the FRW bridge subjected to the high axle loadings prescribed in AS 5100 is examined through performance load testing. Both the static and the moving load tests are carried out using a fully laden commonly available three-axle tandem truck. The bridge deck is extensively strain gauged and displacement at several key locations is measured using linear variable displacement transducers (LVDTs). A high speed camera is used in the performance test and the digital image data are analysed using proprietary software to capture the locations of the wheel positions on the bridge span accurately. The wheel location is thus synchronised with the displacement and strain time series to infer the structural response of the FRW bridge. Field test data are used to calibrate a grillage model, developed for further analysis of the FRW bridge to various sets of high axle loads stipulated in the bridge design standard. Bridge behaviour predicted by the grillage model has exemplified that the live load stresses of the FRW bridge is significantly lower than the yield strength of steel and the deflections are well below the serviceability limit state set out in AS 5100. Based on the results reported in this thesis, it is concluded that the disused FRWs are competent to resist high axle loading prescribed in AS 5100 and are a viable alternative structural solution of bridge deck in the context of the low volume road networks.

Reactive image-based collision avoidance system for unmanned aircraft systems

Approximately 20 years have passed now since the NTSB issued its original recommendation to expedite development, certification and production of low-cost proximity warning and conflict detection systems for general aviation [1]. While some systems are in place (TCAS [2]), ¡¨see-and-avoid¡¨ remains the primary means of separation between light aircrafts sharing the national airspace. The requirement for a collision avoidance or sense-and-avoid capability onboard unmanned aircraft has been identified by leading government, industry and regulatory bodies as one of the most significant challenges facing the routine operation of unmanned aerial systems (UAS) in the national airspace system (NAS) [3, 4]. In this thesis, we propose and develop a novel image-based collision avoidance system to detect and avoid an upcoming conflict scenario (with an intruder) without first estimating or filtering range. The proposed collision avoidance system (CAS) uses relative bearing ƒÛ and angular-area subtended ƒê , estimated from an image, to form a test statistic AS C . This test statistic is used in a thresholding technique to decide if a conflict scenario is imminent. If deemed necessary, the system will command the aircraft to perform a manoeuvre based on ƒÛ and constrained by the CAS sensor field-of-view. Through the use of a simulation environment where the UAS is mathematically modelled and a flight controller developed, we show that using Monte Carlo simulations a probability of a Mid Air Collision (MAC) MAC RR or a Near Mid Air Collision (NMAC) RiskRatio can be estimated. We also show the performance gain this system has over a simplified version (bearings-only ƒÛ ). This performance gain is demonstrated in the form of a standard operating characteristic curve. Finally, it is shown that the proposed CAS performs at a level comparable to current manned aviations equivalent level of safety (ELOS) expectations for Class E airspace. In some cases, the CAS may be oversensitive in manoeuvring the owncraft when not necessary, but this constitutes a more conservative and therefore safer, flying procedures in most instances.

Vision based control for fixed wing UAVs inspecting locally linear infrastructure using skid-to-turn maneuvers

The following paper proposes a novel application of Skid-to-Turn maneuvers for fixed wing Unmanned Aerial Vehicles (UAVs) inspecting locally linear infrastructure. Fixed wing UAVs, following the design of manned aircraft, traditionally employ Bank-to-Turn maneuvers to change heading and thus direction of travel. Commonly overlooked is the effect these maneuvers have on downward facing body fixed sensors, which as a result of bank, point away from the feature during turns. By adopting Skid-to-Turn maneuvers, the aircraft is able change heading whilst maintaining wings level flight, thus allowing body fixed sensors to maintain a downward facing orientation. Eliminating roll also helps to improve data quality, as sensors are no longer subjected to the swinging motion induced as they pivot about an axis perpendicular to their line of sight. Traditional tracking controllers that apply an indirect approach of capturing ground based data by flying directly overhead can also see the feature off center due to steady state pitch and roll required to stay on course. An Image Based Visual Servo controller is developed to address this issue, allowing features to be directly tracked within the image plane. Performance of the proposed controller is tested against that of a Bank-to-Turn tracking controller driven by GPS derived cross track error in a simulation environment developed to simulate the field of view of a body fixed camera.

Scene invariant crowd counting and crowd occupancy analysis

In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult. In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data. Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist.

Chinese driver perceptions about speeding and traffic law enforcement

The World Health Organisation has highlighted the urgent need to address the escalating global public health crisis associated with road trauma. Low-income and middle-income countries bear the brunt of this, and rapid increases in private vehicle ownership in these nations present new challenges to authorities, citizens, and researchers alike. The role of human factors in the road safety equation is high. In China, human factors have been implicated in more than 90% of road crashes, with speeding identified as the primary cause (Wang, 2003). However, research investigating the factors that influence driving speeds in China is lacking (WHO, 2004). To help address this gap, we present qualitative findings from group interviews conducted with 35 Beijing car drivers in 2008. Some themes arising from data analysis showed strong similarities with findings from highly-motorised nations (e.g., UK, USA, and Australia) and include issues such as driver definitions of ‘speeding’ that appear to be aligned with legislative enforcement tolerances, factors relating to ease/difficulty of speed limit compliance, and the modifying influence of speed cameras. However, unique differences were evident, some of which, to our knowledge, are previously unreported in research literature. Themes included issues relating to an expressed lack of understanding about why speed limits are necessary and a perceived lack of transparency in traffic law enforcement and use of associated revenue. The perception of an unfair system seemed related to issues such as differential treatment of certain drivers and the large amount of individual discretion available to traffic police when administering sanctions. Additionally, a wide range of strategies to overtly avoid detection for speeding and/or the associated sanctions were reported. These strategies included the use of in-vehicle speed camera detectors, covering or removing vehicle licence number plates, and using personal networks of influential people to reduce or cancel a sanction. These findings have implications for traffic law, law enforcement, driver training, and public education in China. While not representative of all Beijing drivers, we believe that these research findings offer unique insights into driver behaviour in China.

Jams, jelly beans and the fruits of passion - art book (26 Pages)

Statement: Jams, Jelly Beans and the Fruits of Passion Let us search, instead, for an epistemology of practice implicit in the artistic, intuitive processes which some practitioners do bring to situations of uncertainty, instability, uniqueness, and value conflict. (Schön 1983, p40) Game On was born out of the idea of creative community; finding, networking, supporting and inspiring the people behind the face of an industry, those in the mist of the machine and those intending to join. We understood this moment to be a pivotal opportunity to nurture a new emerging form of game making, in an era of change, where the old industry models were proving to be unsustainable. As soon as we started putting people into a room under pressure, to make something in 48hrs, a whole pile of evolutionary creative responses emerged. People refashioned their craft in a moment of intense creativity that demanded different ways of working, an adaptive approach to the craft of making games – small – fast – indie. An event like the 48hrs forces participants’ attention onto the process as much as the outcome. As one game industry professional taking part in a challenge for the first time observed: there are three paths in the genesis from idea to finished work: the path that focuses on mechanics; the path that focuses on team structure and roles, and the path that focuses on the idea, the spirit – and the more successful teams put the spirit of the work first and foremost. The spirit drives the adaptation, it becomes improvisation. As Schön says: “Improvisation consists on varying, combining and recombining a set of figures within the schema which bounds and gives coherence to the performance.” (1983, p55). This improvisational approach is all about those making the games: the people and the principles of their creative process. This documentation evidences the intensity of their passion, determination and the shit that they are prepared to put themselves through to achieve their goal – to win a cup full of jellybeans and make a working game in 48hrs. 48hr is a project where, on all levels, analogue meets digital. This concept was further explored through the documentation process. All of these pictures were taken with a 1945 Leica III camera. The use of this classic, film-based camera, gives the images a granularity and depth, this older slower technology exposes the very human moments of digital creativity. ____________________________ Schön, D. A. 1983, The Reflective Practitioner: How Professionals Think in Action, Basic Books, New York

A suspicious behaviour detection using a context space model for smart surveillance systems

Video surveillance systems using Closed Circuit Television (CCTV) cameras, is one of the fastest growing areas in the field of security technologies. However, the existing video surveillance systems are still not at a stage where they can be used for crime prevention. The systems rely heavily on human observers and are therefore limited by factors such as fatigue and monitoring capabilities over long periods of time. This work attempts to address these problems by proposing an automatic suspicious behaviour detection which utilises contextual information. The utilisation of contextual information is done via three main components: a context space model, a data stream clustering algorithm, and an inference algorithm. The utilisation of contextual information is still limited in the domain of suspicious behaviour detection. Furthermore, it is nearly impossible to correctly understand human behaviour without considering the context where it is observed. This work presents experiments using video feeds taken from CAVIAR dataset and a camera mounted on one of the buildings Z-Block) at the Queensland University of Technology, Australia. From these experiments, it is shown that by exploiting contextual information, the proposed system is able to make more accurate detections, especially of those behaviours which are only suspicious in some contexts while being normal in the others. Moreover, this information gives critical feedback to the system designers to refine the system.

The social orders of family mealtime

This study examined the everyday practices of families within the context of family mealtime to investigate how members accomplished mealtime interactions. Using an ethnomethodological approach, conversation analysis and membership categorization analysis, the study investigated the interactional resources that family members used to assemble their social orders moment by moment during family mealtimes. While there is interest in mealtimes within educational policy, health research and the media, there remain few studies that provide fine-grained detail about how members produce the social activity of having a family meal. Findings from this study contribute empirical understandings about families and family mealtime. Two families with children aged 2 to 10 years were observed as they accomplished their everyday mealtime activities. Data collection took place in the family homes where family members video recorded their naturally occurring mealtimes. Each family was provided with a video camera for a one-month period and they decided which mealtimes they recorded, a method that afforded participants greater agency in the data collection process and made available to the analyst a window into the unfolding of the everyday lives of the families. A total of 14 mealtimes across the two families were recorded, capturing 347 minutes of mealtime interactions. Selected episodes from the data corpus, which includes centralised breakfast and dinnertime episodes, were transcribed using the Jeffersonian system. Three data chapters examine extended sequences of family talk at mealtimes, to show the interactional resources used by members during mealtime interactions. The first data chapter explores multiparty talk to show how the uniqueness of the occasion of having a meal influences turn design. It investigates the ways in which members accomplish two-party talk within a multiparty setting, showing how one child "tells" a funny story to accomplish the drawing together of his brothers as an audience. As well, this chapter identifies the interactional resources used by the mother to cohort her children to accomplish the choralling of grace. The second data chapter draws on sequential and categorical analysis to show how members are mapped to a locally produced membership category. The chapter shows how the mapping of members into particular categories is consequential for social order; for example, aligning members who belong to the membership category "had haircuts" and keeping out those who "did not have haircuts". Additional interactional resources such as echoing, used here to refer to the use of exactly the same words, similar prosody and physical action, and increasing physical closeness, are identified as important to the unfolding talk particularly as a way of accomplishing alignment between the grandmother and grand-daughter. The third and final data analysis chapter examines topical talk during family mealtimes. It explicates how members introduce topics of talk with an orientation to their co-participant and the way in which the take up of a topic is influenced both by the sequential environment in which it is introduced and the sensitivity of the topic. Together, these three data chapters show aspects of how family members participated in family mealtimes. The study contributes four substantive themes that emerged during the analytic process and, as such, the themes reflect what the members were observed to be doing. The first theme identified how family knowledge was relevant and consequential for initiating and sustaining interaction during mealtime with, for example, members buying into the talk of other members or being requested to help out with knowledge about a shared experience. Knowledge about members and their activities was evident with the design of questions evidencing an orientation to coparticipant’s knowledge. The second theme found how members used topic as a resource for social interaction. The third theme concerned the way in which members utilised membership categories for producing and making sense of social action. The fourth theme, evident across all episodes selected for analysis, showed how children’s competence is an ongoing interactional accomplishment as they manipulated interactional resources to manage their participation in family mealtime. The way in which children initiated interactions challenges previous understandings about children’s restricted rights as conversationalists. As well as making a theoretical contribution, the study offers methodological insight by working with families as research participants. The study shows the procedures involved as the study moved from one where the researcher undertook the decisions about what to videorecord to offering this decision making to the families, who chose when and what to videorecord of their mealtime practices. Evident also are the ways in which participants orient both to the video-camera and to the absent researcher. For the duration of the mealtime the video-camera was positioned by the adults as out of bounds to the children; however, it was offered as a "treat" to view after the mealtime was recorded. While situated within family mealtimes and reporting on the experiences of two families, this study illuminates how mealtimes are not just about food and eating; they are social. The study showed the constant and complex work of establishing and maintaining social orders and the rich array of interactional resources that members draw on during family mealtimes. The family’s interactions involved members contributing to building the social orders of family mealtime. With mealtimes occurring in institutional settings involving young children, such as long day care centres and kindergartens, the findings of this study may help educators working with young children to see the rich interactional opportunities mealtimes afford children, the interactional competence that children demonstrate during mealtimes, and the important role/s that adults may assume as co-participants in interactions with children within institutional settings.

Outdoor simultaneous localisation and mapping using RatSLAM

In this paper an existing method for indoor Simultaneous Localisation and Mapping (SLAM) is extended to operate in large outdoor environments using an omnidirectional camera as its principal external sensor. The method, RatSLAM, is based upon computational models of the area in the rat brain that maintains the rodent’s idea of its position in the world. The system uses the visual appearance of different locations to build hybrid spatial-topological maps of places it has experienced that facilitate relocalisation and path planning. A large dataset was acquired from a dynamic campus environment and used to verify the system’s ability to construct representations of the world and simultaneously use these representations to maintain localisation.

Graph rigidity for near-coplanar structure from motion

Recent algorithms for monocular motion capture (MoCap) estimate weak-perspective camera matrices between images using a small subset of approximately-rigid points on the human body (i.e. the torso and hip). A problem with this approach, however, is that these points are often close to coplanar, causing canonical linear factorisation algorithms for rigid structure from motion (SFM) to become extremely sensitive to noise. In this paper, we propose an alternative solution to weak-perspective SFM based on a convex relaxation of graph rigidity. We demonstrate the success of our algorithm on both synthetic and real world data, allowing for much improved solutions to marker less MoCap problems on human bodies. Finally, we propose an approach to solve the two-fold ambiguity over bone direction using a k-nearest neighbour kernel density estimator.

Learning informative features for indoor traversability

This paper presents a method for automatic terrain classification, using a cheap monocular camera in conjunction with a robot’s stall sensor. A first step is to have the robot generate a training set of labelled images. Several techniques are then evaluated for preprocessing the images, reducing their dimensionality, and building a classifier. Finally, the classifier is implemented and used online by an indoor robot. Results are presented, demonstrating an increased level of autonomy.

Performance testing of road bridge deck containing flat rail wagons

A road bridge containing disused flatbed rail wagons as the primary deck superstructure was performance tested in a low volume, high axle load traffic road in Queensland, Australia; some key results are presented in this paper. A fully laden truck of total weight 28.88 % of the serviceability design load prescribed in the Australian bridge code was used; its wheel positions were accurately captured using a high speed camera and synchronised with the real‐time deflections and strains measured at the critical members of the flat rail wagons. The strains remained well below the yield and narrated the existence of composite action between the reinforced concrete slab pavement and the wagon deck. A three dimensional grillage model was developed and calibrated using the test data, which established the structural adequacy of the rail wagons and the positive contribution of the reinforced concrete slab pavement to resist high axle traffic loads on a single lane bridge in the low volume roads network.

Gaussian process models for sensor-centric robot localisation

This paper presents an approach to building an observation likelihood function from a set of sparse, noisy training observations taken from known locations by a sensor with no obvious geometric model. The basic approach is to fit an interpolant to the training data, representing the expected observation, and to assume additive sensor noise. This paper takes a Bayesian view of the problem, maintaining a posterior over interpolants rather than simply the maximum-likelihood interpolant, giving a measure of uncertainty in the map at any point. This is done using a Gaussian process framework. To validate the approach experimentally, a model of an environment is built using observations from an omni-directional camera. After a model has been built from the training data, a particle filter is used to localise while traversing this environment