Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.

Laser-camera data discrepancies and reliable perception in outdoor robotics

This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated and propagated up to the projection of the laser points onto the image. Then, for each pair of laser scan-camera image acquired, the information at corners of the laser scan is compared with the content of the image, resulting in a likelihood of correspondence. The result of this process is then used to validate segments of the laser scan that are found to be consistent with the image, while inconsistent segments are rejected. Experimental results illustrate how this technique can improve the reliability of perception in challenging environmental conditions, such as in the presence of airborne dust.

Publishing, postage, and prizes : classic Australian children’s literature in the public eye

2012 saw the publication of competing and complementary lines of Australian “classics”: “A&R Australian Classics” (HarperCollins) and “Text Classics” (Text Publishing). While Angus and Robertson were key in establishing a canon of Australian children’s classics in the twentieth century, it was the Text Classics line which included a selection of young people’s titles in their 2013. In turn, Penguin Australia launched a selection of “Australian Children’s Classics”. In so doing, these publishers were drawing on particular literary and visual cultural traditions in Australian children’s literature. Public assertions of a particular selection of children’s books reveals not only contemporary assumptions about desirable childhood experiences but about the operation of nostalgia therein. In encouraging Australian adults to judge books by their covers, such gestures imply that Australian children may be similarly understood. Importantly, the illusion of unity, sameness, and legibility which is promised by circumscribed canons of “classic” children’s literature may well imply a desire for similarly illusory, unified, legible, “classic” childhood. This paper attends to public attempts to materialise (and legitimise) a canon of classic Australian children’s literature. In particular, it considers the ways in which publishing, postage stamps, and book awards make visible a range of children’s books, but do so in order to either fix or efface the content or meaning of the books themselves. Moving between assertions of the best books for children from the 1980s to today, and of the social values circulated within those books, this paper considers the possibilities and problematics of an Australian children’s canon.

Digital Literacy and the Spaces of Academic Discourse

Digital literacy poses a particular challenge to the research-led university. Although these universities are often at the forefront of introducing digital literacy initiatives—such as e-learning platforms, technological infrastructure, and digital repositories—these applications of digital literacy tend to be more instrumental or functional than critical or creative. Certainly, this clash of cultures between the instrumental/functional and the critical/analytical is at the heart of debates over the uses of digital literacy in higher education. However, this simple equation of political forces with instrumentality and the corresponding equation of the university with a tradition of reflective thought that brings criticism to bear on instrumentality elide the fact that this conflict is more deeply rooted within the academy. This essay argues that, in fact, much of the resistance to critical uses of digital literacy comes from within the institution of the university itself. That is, the university is bound up in a scriptural economy that prioritises the printed word and that reinforces its power by way of a normative, political, and spatialised academic discourse. It is this print-based scriptural economy—in which this essay must acknowledge its own complicity—that a critical approach to digital literacy threatens to disrupt or lay bare.

Features-pooling blind jpeg image steganalysis

In this research, we introduce a new blind steganalysis in detecting grayscale JPEG images. Features-pooling method is employed to extract the steganalytic features and the classification is done by using neural network. Three different steganographic models are tested and classification results are compared to the five state-of-the-art blind steganalysis.

Visible and near infrared spectroscopy of hayabusa reentry using semi-autonomous tracking

Aground-based tracking camera and coaligned slitless spectrograph were used to measure the spectral signature of visible radiation emitted from the Hayabusa capsule as it entered into the Earth’s atmosphere in June 2010. Good quality spectra were obtained, which showed the presence of radiation from the heat shield of the vehicle and the shock-heated air in front of the vehicle. An analysis of the blackbody nature of the radiation concluded that the peak average temperature of the surface was about (3100± 100)K. Line spectra from oxygen and nitrogen atoms were used to infer a peak average shock-heated gas temperature of around((7000±400))K.

Requiem for a beast : a case study in controversy

In 2008, Matt Ottley’s Requiem for a Beast: A Work for Image, Word and Music was awarded the Book of the Year: Picture Book by the Children’s Book Council of Australia (CBCA). Ottley’s book is challenging in its form and content: it uses words, illustrations, and music to tell a sustained, multi-layered narrative about one young man’s attempts to reconcile his family’s and his nation’s shameful history of violence against Aboriginal Australians, while also coming to terms with his own attempts to commit suicide. Given the ways in which the CBCA’s annual book awards are used by teachers, librarians, and parents to select the “best” books for young readers, it is unsurprising that the prizing of Requiem for a Beast stirred up controversy. Responses to the book proliferated across professional and popular outlets—it even received coverage on an Australian tabloid television program—and initiated a variety of conversations about what constitutes appropriate reading for young people. Perhaps more significantly, the controversy over Requiem winning picture book of the year forced the CBCA, teacher librarians, and caregivers to examine (and, often, defend) their roles and responsibilities in the circulation and promotion of children’s literature. This paper reads the Requiem controversies as a case study for understanding the complementary and contradictory roles of institutions and individuals in the ethical circulation of children’s literature in contemporary Australia and beyond.

Renormalization group interpretation of the Born and Rytov approximations

In this paper the method of renormalization group (RG) [Phys. Rev. E 54, 376 (1996)] is related to the well-known approximations of Rytov and Born used in wave propagation in deterministic and random media. Certain problems in linear and nonlinear media are examined from the viewpoint of RG and compared with the literature on Born and Rytov approximations. It is found that the Rytov approximation forms a special case of the asymptotic expansion generated by the RG, and as such it gives a superior approximation to the exact solution compared with its Born counterpart. Analogous conclusions are reached for nonlinear equations with an intensity-dependent index of refraction where the RG recovers the exact solution. © 2008 Optical Society of America.

Do spoken nonword and sentence repetition tasks discriminate language impairment in children with an ASD?

The primary aim of this paper was to investigate heterogeneity in language abilities of children with a confirmed diagnosis of an ASD (N = 20) and children with typical development (TD; N = 15). Group comparisons revealed no differences between ASD and TD participants on standard clinical assessments of language ability, reading ability or nonverbal intelligence. However, a hierarchical cluster analysis based on spoken nonword repetition and sentence repetition identified two clusters within the combined group of ASD and TD participants. The first cluster (N = 6) presented with significantly poorer performances than the second cluster (N = 29) on both of the clustering variables in addition to single word and nonword reading. The significant differences between the two clusters occur within a context of Cluster 1 having language impairment and a tendency towards more severe autistic symptomatology. Differences between the oral language abilities of the first and second clusters are considered in light of diagnosis, attention and verbal short term memory skills and reading impairment.

Pedestrian dynamics in real and simulated world

The paper examines the knowledge of pedestrian movements, both in real scenarios, and from more recent years, in the virtual 4 simulation realm. Aiming to verify whether it is possible to learn from the study of virtual environments how people will behave in real 5 environments, it is vital to understand what is already known about behavior in real environments. Besides the walking interaction among 6 pedestrians, the interaction between pedestrians and the built environment in which they are walking also have greatest relevance. Force-based 7 models were compared with the other three major microscopic models of pedestrian simulation to demonstrate a more realistic and capable 8 heuristic approach is needed for the study of the dynamics of pedestrians.

Simultaneous localization and planning on multiple map hypotheses

This paper presents a novel method to rank map hypotheses by the quality of localization they afford. The highest ranked hypothesis at any moment becomes the active representation that is used to guide the robot to its goal location. A single static representation is insufficient for navigation in dynamic environments where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners. In our approach we simultaneously rank multiple map hypotheses by the influence that localization in each of them has on locally accurate odometry. This is done online for the current locally accurate window by formulating a factor graph of odometry relaxed by localization constraints. Comparison of the resulting perturbed odometry of each hypothesis with the original odometry yields a score that can be used to rank map hypotheses by their utility. We deploy the proposed approach on a real robot navigating a structurally noisy office environment. The configuration of the environment is physically altered outside the robots sensory horizon during navigation tasks to demonstrate the proposed approach of hypothesis selection.

Topic dependent language modelling for spoken term detection

This paper investigates the effect of topic dependent language models (TDLM) on phonetic spoken term detection (STD) using dynamic match lattice spotting (DMLS). Phonetic STD consists of two steps: indexing and search. The accuracy of indexing audio segments into phone sequences using phone recognition methods directly affects the accuracy of the final STD system. If the topic of a document in known, recognizing the spoken words and indexing them to an intermediate representation is an easier task and consequently, detecting a search word in it will be more accurate and robust. In this paper, we propose the use of TDLMs in the indexing stage to improve the accuracy of STD in situations where the topic of the audio document is known in advance. It is shown that using TDLMs instead of the traditional general language model (GLM) improves STD performance according to figure of merit (FOM) criteria.

An evaluation of crowd counting methods, features and regression models

Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

Multi-modal deformable medical image registration

Non-rigid image registration is an essential tool required for overcoming the inherent local anatomical variations that exist between images acquired from different individuals or atlases. Furthermore, certain applications require this type of registration to operate across images acquired from different imaging modalities. One popular local approach for estimating this registration is a block matching procedure utilising the mutual information criterion. However, previous block matching procedures generate a sparse deformation field containing displacement estimates at uniformly spaced locations. This neglects to make use of the evidence that block matching results are dependent on the amount of local information content. This paper presents a solution to this drawback by proposing the use of a Reversible Jump Markov Chain Monte Carlo statistical procedure to optimally select grid points of interest. Three different methods are then compared to propagate the estimated sparse deformation field to the entire image including a thin-plate spline warp, Gaussian convolution, and a hybrid fluid technique. Results show that non-rigid registration can be improved by using the proposed algorithm to optimally select grid points of interest.