Modeling collision avoidance decisions in navigation

Due to grave potential human, environmental and economical consequences of collisions at sea, collision avoidance has become an important safety concern in navigation. To reduce the risk of collisions at sea, appropriate collision avoidance actions need to be taken in accordance with the regulations, i.e., International Regulations for Preventing Collisions at Sea. However, the regulations only provide qualitative rules and guidelines, and therefore it requires navigators to decide on collision avoidance actions quantitatively by using their judgments which often leads to making errors in navigation. To better help navigators in collision avoidance, this paper develops a comprehensive collision avoidance decision making model for providing whether a collision avoidance action is required, when to take action and what action to be taken. The model is developed based on three types of collision avoidance actions, such as course change only, speed change only, and a combination of both. The model has potential to reduce the chance of making human error in navigation by assisting navigators in decision making on collision avoidance actions.

Evaluation of fibroin-based scaffolds for ocular tissue reconstruction

The epithelium of the corneolimbus contains stem cells for regenerating the corneal epithelium. Diseases and injuries affecting the limbus can lead to a condition known as limbal stem cell deficiency (LSCD), which results in loss of the corneal epithelium, and subsequent chronic inflammation and scarring of the ocular surface. Advances in the treatment of LSCD have been achieved through use of cultured human limbal epithelial (HLE) grafts to restore epithelial stem cells of the ocular surface. These epithelial grafts are usually produced by the ex vivo expansion of HLE cells on human donor amniotic membrane (AM), but this is not without limitations. Although AM is the most widely accepted substratum for HLE transplantation, donor variation, risk of disease transfer, and rising costs have led to the search for alternative biomaterials to improve the surgical outcome of LSCD. Recent studies have demonstrated that Bombyx mori silk fibroin (hereafter referred to as fibroin) membranes support the growth of primary HLE cells, and thus this thesis aims to explore the possibility of using fibroin as a biomaterial for ocular surface reconstruction. Optimistically, the grafted sheets of cultured epithelium would provide a replenishing source of epithelial progenitor cells for maintaining the corneal epithelium, however, the HLE cells lose their progenitor cell characteristics once removed from their niche. More severe ocular surface injuries, which result in stromal scarring, damage the epithelial stem cell niche, which subsequently leads to poor corneal re-epithelialisation post-grafting. An ideal solution to repairing the corneal limbus would therefore be to grow and transplant HLE cells on a biomaterial that also provides a means for replacing underlying stromal cells required to better simulate the normal stem cell niche. The recent discovery of limbal mesenchymal stromal cells (L-MSC) provides a possibility for stromal repair and regeneration, and therefore, this thesis presents the use of fibroin as a possible biomaterial to support a three dimensional tissue engineered corneolimbus with both an HLE and underlying L-MSC layer. Investigation into optimal scaffold design is necessary, including adequate separation of epithelial and stromal layers, as well as direct cell-cell contact. Firstly, the attachment, morphology and phenotype of HLE cells grown on fibroin were directly compared to that observed on donor AM, the current clinical standard substrate for HLE transplantation. The production, transparency, and permeability of fibroin membranes were also evaluated in this part of the study. Results revealed that fibroin membranes could be routinely produced using a custom-made film casting table and were found to be transparent and permeable. Attachment of HLE cells to fibroin after 4 hours in serum-free medium was similar to that supported by tissue culture plastic but approximately 6-fold less than that observed on AM. While HLE cultured on AM displayed superior stratification, epithelia constructed from HLE on fibroin maintained evidence of corneal phenotype (cytokeratin pair 3/12 expression; CK3/12) and displayed a comparable number and distribution of ÄNp63+ progenitor cells to that seen in cultures grown on AM. These results confirm the suitability of membranes constructed from silk fibroin as a possible substrate for HLE cultivation. One of the most important aspects in corneolimbal tissue engineering is to consider the reconstruction of the limbal stem cell niche to help form the natural limbus in situ. MSC with similar properties to bone marrow derived-MSC (BM-MSC) have recently been grown from the limbus of the human cornea. This thesis evaluated methods for culturing L-MSC and limbal keratocytes using various serum-free media. The phenotype of resulting cultures was examined using photography, flow cytometry for CD34 (keratocyte marker), CD45 (bone marrow-derived cell marker), CD73, CD90, CD105 (collectively MSC markers), CD141 (epithelial/vascular endothelial marker), and CD271 (neuronal marker), immunocytochemistry (alpha-smooth muscle actin; á-sma), differentiation assays (osteogenesis, adipogenesis and chrondrogenesis), and co-culture experiments with HLE cells. While all techniques supported to varying degrees establishment of keratocyte and L-MSC cultures, sustained growth and serial propagation was only achieved in serum-supplemented medium or the MesenCult-XF„¥ culture system (Stem Cell Technologies). Cultures established in MesenCult-XF„¥ grew faster than those grown in serum-supplemented medium and retained a more optimal MSC phenotype. L-MSC cultivated in MesenCult-XFR were also positive for CD141, rarely expressed £\-sma, and displayed multi-potency. L-MSC supported growth of HLE cells, with the largest epithelial islands being observed in the presence of L-MSC established in MesenCult-XF„¥ medium. All HLE cultures supported by L-MSC widely expressed the progenitor cell marker £GNp63, along with the corneal differentiation marker CK3/12. Our findings conclude that MesenCult-XFR is a superior culture system for L-MSC, but further studies are required to explore the significance of CD141 expression in these cells. Following on from the findings of the previous two parts, silk fibroin was tested as a novel dual-layer construct containing both an epithelium and underlying stroma for corneolimbal reconstruction. In this section, the growth and phenotype of HLE cells on non-porous versus porous fibroin membranes was compared. Furthermore, the growth of L-MSC in either serum-supplemented medium or the MesenCult-XFR culture system within fibroin fibrous mats was investigated. Lastly, the co-culture of HLE and L-MSC in serum-supplemented medium on and within fibroin dual-layer constructs was also examined. HLE on porous membranes displayed a flattened and squamous monolayer; in contrast, HLE on non-porous fibroin appeared cuboidal and stratified closer in appearance to a normal corneal epithelium. Both constructs maintained CK3/12 expression and distribution of £GNp63+ progenitor cells. Dual-layer fibroin scaffolds consisting of HLE cells and L-MSC maintained a similar phenotype as on the single layers alone. Overall, the present study proposed to create a three dimensional limbal tissue substitute of HLE cells and L-MSC together, ultimately for safe and beneficial transplantation back into the human eye. The results show that HLE and L-MSC can be cultivated separately and together whilst maintaining a clinically feasible phenotype containing a majority of progenitor cells. In addition, L-MSC were able to be cultivated routinely in the MesenCult-XF® culture system while maintaining a high purity for the MSC characteristic phenotype. However, as a serum-free culture medium was not found to sustain growth of both HLE and L-MSC, the combination scaffold was created in serum-supplemented medium, indicating that further refinement of this cultured limbal scaffold is required. This thesis has also demonstrated a potential novel marker for L-MSC, and has generated knowledge which may impact on the understanding of stromal-epithelial interactions. These results support the feasibility of a dual-layer tissue engineered corneolimbus constructed from silk fibroin, and warrant further studies into the potential benefits it offers to corneolimbal tissue regeneration. Further refinement of this technology should explore the potential benefits of using epithelial-stromal co-cultures with MesenCult-XF® derived L-MSC. Subsequent investigations into the effects of long-term culture on the phenotype and behaviour of the cells in the dual-layer scaffolds are also required. While this project demonstrated the feasibility in vitro for the production of a dual-layer tissue engineered corneolimbus, further studies are required to test the efficacy of the limbal scaffold in vivo. Future in vivo studies are essential to fully understand the integration and degradation of silk fibroin biomaterials in the cornea over time. Subsequent experiments should also investigate the use of both AM and silk fibroin with epithelial and stromal cell co-cultures in an animal model of LSCD. The outcomes of this project have provided a foundation for research into corneolimbal reconstruction using biomaterials and offer a stepping stone for future studies into corneolimbal tissue engineering.

Neural network-based detection of virtual environment anomalies

The increasingly widespread use of large-scale 3D virtual environments has translated into an increasing effort required from designers, developers and testers. While considerable research has been conducted into assisting the design of virtual world content and mechanics, to date, only limited contributions have been made regarding the automatic testing of the underpinning graphics software and hardware. In the work presented in this paper, two novel neural network-based approaches are presented to predict the correct visualization of 3D content. Multilayer perceptrons and self-organizing maps are trained to learn the normal geometric and color appearance of objects from validated frames and then used to detect novel or anomalous renderings in new images. Our approach is general, for the appearance of the object is learned rather than explicitly represented. Experiments were conducted on a game engine to determine the applicability and effectiveness of our algorithms. The results show that the neural network technology can be effectively used to address the problem of automatic and reliable visual testing of 3D virtual environments.

Microscopic cooperative traffic based on NGSIM data

The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Vehicles are able to communicate on the local traffic state in real time, which could result in an automatic and therefore better reaction to the mechanism of traffic jam formation. An upstream single hop radio broadcast network can improve the perception of each cooperative driver within radio range and hence the traffic stability. The impact of a cooperative law on traffic congestion appearance is investigated, analytically and through simulation. Ngsim field data is used to calibrate the Optimal Velocity with Relative Velocity (OVRV) car following model and the MOBIL lane-changing model is implemented. Assuming that congestion can be triggered either by a perturbation in the instability domain or by a critical lane changing behavior, the calibrated car following behavior is used to assess the impact of a microscopic cooperative law on abnormal lane changing behavior. The cooperative law helps reduce and delay traffic congestion as it increases traffic flow stability.

Towards brain-based sensor fusion for navigating robots

Current state of the art robot mapping and navigation systems produce impressive performance under a narrow range of robot platform, sensor and environmental conditions, in contrast to animals such as rats that produce “good enough” maps that enable them to function under an incredible range of situations. In this paper we present a rat-inspired featureless sensor-fusion system that assesses the usefulness of multiple sensor modalities based on their utility and coherence for place recognition during a navigation task, without knowledge as to the type of sensor. We demonstrate the system on a Pioneer robot in indoor and outdoor environments with abrupt lighting changes. Through dynamic weighting of the sensors, the system is able to perform correct place recognition and mapping where the static sensor weighting approach fails.

Heteroscedastic probabilistic linear discriminant analysis for manifold learning in video-based face recognition

To recognize faces in video, face appearances have been widely modeled as piece-wise local linear models which linearly approximate the smooth yet non-linear low dimensional face appearance manifolds. The choice of representations of the local models is crucial. Most of the existing methods learn each local model individually meaning that they only anticipate variations within each class. In this work, we propose to represent local models as Gaussian distributions which are learned simultaneously using the heteroscedastic probabilistic linear discriminant analysis (PLDA). Each gallery video is therefore represented as a collection of such distributions. With the PLDA, not only the within-class variations are estimated during the training, the separability between classes is also maximized leading to an improved discrimination. The heteroscedastic PLDA itself is adapted from the standard PLDA to approximate face appearance manifolds more accurately. Instead of assuming a single global within-class covariance, the heteroscedastic PLDA learns different within-class covariances specific to each local model. In the recognition phase, a probe video is matched against gallery samples through the fusion of point-to-model distances. Experiments on the Honda and MoBo datasets have shown the merit of the proposed method which achieves better performance than the state-of-the-art technique.

A recommendation for designing mobile pedestrian navigation system in university campuses

University campuses have thousands of new students, staff and visitors every year. For those who are unfamiliar with the campus environment, an effective pedestrian navigation system is essential to orientate and guide them around the campus. Compared to traditional navigation systems, such as physical signposts and digital map kiosks, a mobile pedestrian navigation system provides advantages in terms of mobility, sensing capabilities, weather-awareness when the user is on the go. However, how best to design a mobile pedestrian navigation system for university campuses is still vague due to limited research in understanding how pedestrians interact with the system, and what information is required for traveling in a complex environment such as university campus. In this paper, we present a mobile pedestrian navigation system called QUT Nav. A field study with eight participants was run in a university campus context, aiming to identify key information required in a mobile pedestrian navigation system for user traveling in university campuses. It also investigated user's interactions and behaviours while they were navigating in the campus environment. Based on the results from the field study, a recommendation for designing mobile pedestrian navigation systems for university campuses is stated.

Robust vision-based underwater homing using self-similar landmarks

Next-generation autonomous underwater vehicles (AUVs) will be required to robustly identify underwater targets for tasks such as inspection, localization, and docking. Given their often unstructured operating environments, vision offers enormous potential in underwater navigation over more traditional methods; however, reliable target segmentation often plagues these systems. This paper addresses robust vision-based target recognition by presenting a novel scale and rotationally invariant target design and recognition routine based on self-similar landmarks that enables robust target pose estimation with respect to a single camera. These algorithms are applied to an AUV with controllers developed for vision-based docking with the target. Experimental results show that the system performs exceptionally on limited processing power and demonstrates how the combined vision and controller system enables robust target identification and docking in a variety of operating conditions.

Spectroscopic correlation analysis of NMR-based metabonomics in exercise science

Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY). Whilst the former has largely been applied to optical spectroscopic analysis, STOCSY was developed and has been applied almost exclusively to NMR metabonomic studies. Using a 1H NMR study of human blood plasma, from subjects recovering from exhaustive exercise trials, the basic concepts and applications of these techniques are examined. Typical information from their application to NMR-based metabonomics is presented and their value in aiding interpretation of NMR data obtained from biological systems is illustrated. Major energy metabolites are identified in the NMR spectra and the dynamics of their appearance and removal from plasma during exercise recovery are illustrated and discussed. The complementary nature of two-dimensional correlation analysis and statistical total correlation spectroscopy are highlighted.

Towards persistent visual navigation using SMART

In this paper, we present SMART (Sequence Matching Across Route Traversals): a vision- based place recognition system that uses whole image matching techniques and odometry information to improve the precision-recall performance, latency and general applicability of the SeqSLAM algorithm. We evaluate the system’s performance on challenging day and night journeys over several kilometres at widely varying vehicle velocities from 0 to 60 km/h, compare performance to the current state-of- the-art SeqSLAM algorithm, and provide parameter studies that evaluate the effectiveness of each system component. Using 30-metre sequences, SMART achieves place recognition performance of 81% recall at 100% precision, outperforming SeqSLAM, and is robust to significant degradations in odometry.

Eight weeks of episodic visual navigation inside a non-stationary environment using adaptive spherical views

This paper presents a long-term experiment where a mobile robot uses adaptive spherical views to localize itself and navigate inside a non-stationary office environment. The office contains seven members of staff and experiences a continuous change in its appearance over time due to their daily activities. The experiment runs as an episodic navigation task in the office over a period of eight weeks. The spherical views are stored in the nodes of a pose graph and they are updated in response to the changes in the environment. The updating mechanism is inspired by the concepts of long- and short-term memories. The experimental evaluation is done using three performance metrics which evaluate the quality of both the adaptive spherical views and the navigation over time.

RatSLAM : using models of rodent hippocampus for robot navigation and beyond

We describe recent biologically-inspired mapping research incorporating brain-based multi-sensor fusion and calibration processes and a new multi-scale, homogeneous mapping framework. We also review the interdisciplinary approach to the development of the RatSLAM robot mapping and navigation system over the past decade and discuss the insights gained from combining pragmatic modelling of biological processes with attempts to close the loop back to biology. Our aim is to encourage the pursuit of truly interdisciplinary approaches to robotics research by providing successful case studies.

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.

Novelty-based visual obstacle detection in agriculture

This paper describes a novel obstacle detection system for autonomous robots in agricultural field environments that uses a novelty detector to inform stereo matching. Stereo vision alone erroneously detects obstacles in environments with ambiguous appearance and ground plane such as in broad-acre crop fields with harvested crop residue. The novelty detector estimates the probability density in image descriptor space and incorporates image-space positional understanding to identify potential regions for obstacle detection using dense stereo matching. The results demonstrate that the system is able to detect obstacles typical to a farm at day and night. This system was successfully used as the sole means of obstacle detection for an autonomous robot performing a long term two hour coverage task travelling 8.5 km.

Moving object detection in aerial video based on spatiotemporal saliency

In this paper, the problem of moving object detection in aerial video is addressed. While motion cues have been extensively exploited in the literature, how to use spatial information is still an open problem. To deal with this issue, we propose a novel hierarchical moving target detection method based on spatiotemporal saliency. Temporal saliency is used to get a coarse segmentation, and spatial saliency is extracted to obtain the object’s appearance details in candidate motion regions. Finally, by combining temporal and spatial saliency information, we can get refined detection results. Additionally, in order to give a full description of the object distribution, spatial saliency is detected in both pixel and region levels based on local contrast. Experiments conducted on the VIVID dataset show that the proposed method is efficient and accurate.