Practical path planning and obstacle avoidance for autonomous mowing

There is a need for systems which can autonomously perform coverage tasks on large outdoor areas. Unfortunately, the state-of-the-art is to use GPS based localization, which is not suitable for precise operations near trees and other obstructions. In this paper we present a robotic platform for autonomous coverage tasks. The system architecture integrates laser based localization and mapping using the Atlas Framework with Rapidly-Exploring Random Trees path planning and Virtual Force Field obstacle avoidance. We demonstrate the performance of the system in simulation as well as with real world experiments.

Automated sensory data alignment for environmental and epidermal change monitoring

In this paper we present research adapting a state of the art condition-invariant robotic place recognition algorithm to the role of automated inter- and intra-image alignment of sensor observations of environmental and skin change over time. The approach involves inverting the typical criteria placed upon navigation algorithms in robotics; we exploit rather than attempt to fix the limited camera viewpoint invariance of such algorithms, showing that approximate viewpoint repetition is realistic in a wide range of environments and medical applications. We demonstrate the algorithms automatically aligning challenging visual data from a range of real-world applications: ecological monitoring of environmental change, aerial observation of natural disasters including flooding, tsunamis and bushfires and tracking wound recovery and sun damage over time and present a prototype active guidance system for enforcing viewpoint repetition. We hope to provide an interesting case study for how traditional research criteria in robotics can be inverted to provide useful outcomes in applied situations.

Representing team behaviours from noisy data using player role

Due to their unobtrusive nature, vision-based approaches to tracking sports players have been preferred over wearable sensors as they do not require the players to be instrumented for each match. Unfortunately however, due to the heavy occlusion between players, variation in resolution and pose, in addition to fluctuating illumination conditions, tracking players continuously is still an unsolved vision problem. For tasks like clustering and retrieval, having noisy data (i.e. missing and false player detections) is problematic as it generates discontinuities in the input data stream. One method of circumventing this issue is to use an occupancy map, where the field is discretised into a series of zones and a count of player detections in each zone is obtained. A series of frames can then be concatenated to represent a set-play or example of team behaviour. A problem with this approach though is that the compressibility is low (i.e. the variability in the feature space is incredibly high). In this paper, we propose the use of a bilinear spatiotemporal basis model using a role representation to clean-up the noisy detections which operates in a low-dimensional space. To evaluate our approach, we used a fully instrumented field-hockey pitch with 8 fixed high-definition (HD) cameras and evaluated our approach on approximately 200,000 frames of data from a state-of-the-art real-time player detector and compare it to manually labeled data.

Searching for semantic person queries using channel representations

It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to relate and easy to understand. However such queries are not easily utilised within intelligent surveillance systems as they are difficult to transform into a representation that can be searched for automatically in large camera networks. In this paper we propose a novel approach that transforms such a semantic query into an avatar that is searchable within a video stream, and demonstrate state-of-the-art performance for locating a subject in video based on a description.

Topical pattern based document modelling and relevance ranking

For traditional information filtering (IF) models, it is often assumed that the documents in one collection are only related to one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling was proposed to generate statistical models to represent multiple topics in a collection of documents, but in a topic model, topics are represented by distributions over words which are limited to distinctively represent the semantics of topics. Patterns are always thought to be more discriminative than single terms and are able to reveal the inner relations between words. This paper proposes a novel information filtering model, Significant matched Pattern-based Topic Model (SPBTM). The SPBTM represents user information needs in terms of multiple topics and each topic is represented by patterns. More importantly, the patterns are organized into groups based on their statistical and taxonomic features, from which the more representative patterns, called Significant Matched Patterns, can be identified and used to estimate the document relevance. Experiments on benchmark data sets demonstrate that the SPBTM significantly outperforms the state-of-the-art models.

A computer generated model of adenosine receptors rationalising binding and selectivity of receptor ligands

Computer graphic analyses on a broad spectrum of adenosine receptor ligands has shown that both the A1 and A2 adenosine receptors have three binding sites. The spatial relationship of these three binding sites has been defined. Adenosine orientation at A1 and A2 is different.

Perceiving the interactive body in dance: Enhancing kinesthetic empathy through art objects

Through a consideration of audience experience of embodiment in contemporary dance performance, this project used kinesthetic empathy as a theoretical construct to inform choreographic decision-making. The research outcome challenged the traditional performer/audience relationship through an interactive dance performance work entitled Planets. This acted as a platform that allowed both audience and performer to collaboratively listen to, process and form movement in a shared kinesthetic state. This connection was enabled through the distribution of interactive art objects, which responded to the shifting proximity between performer and audience. The performance was thus experienced through following a shared goal as instigated by the interactive technology. Through practice-led research, knowledge from kinesthetic empathy, embodied cognition and the mirror neuron system were used to develop the project’s aim in encouraging interactive audiences to engage in movement. This aim influenced studio explorations of movement through an enquiry into the kinesthetic self in dance. Investigations used movement quality, tension, mobility and acceleration to access a familiar movement vocabulary appropriate for a broad interactive audience. This informed the role of the researcher as performer. Planets was developed as a collaborative project between Michael Smith and interactive visual designer Andy Bates and performed over three nights at the Ars Electronica Festival 2014 in Linz, Austria. Supported by documented footage from Planets and audience responses to the performances, this paper draws together the theoretical underpinnings behind the development of the work and includes the experiential perspective of the performer.

Creating good lives through computer games

In this chapter we aim to explore how videogames can lead to improvements in wellbeing. Following Keyes (2007) and Huppert and So (2012) we view wellbeing as a multidimensional concept with both hedonic and eudaimonic aspects. In this chapter we take a broad approach in terms of exploring the impact of videogames on the psychological, social, and physical components of wellbeing. We explore how videogames have been shown to have an impact in each of these domains. Although there is a great deal of evidence for the actual and potential positive impacts of videogames, there are many unanswered questions regarding the situations in which there is likely to be an impact of videogame play on wellbeing, as well as the aspects of wellbeing that are likely to be impacted by videogame play. We conclude the chapter by outlining the key questions for future research. Our focus in this chapter is on the positive influences of videogames. We do not explore research on contexts in which negative impacts are possible or subgroups for which videogames could cause harm. However, these questions are obviously important and we see balanced engagement with age-appropriate videogames as a key prerequisite for any of the wellbeing benefits discussed below.

Bi-modal biometric authentication on mobile phones in challenging conditions

This paper examines the issue of face, speaker and bi-modal authentication in mobile environments when there is significant condition mismatch. We introduce this mismatch by enrolling client models on high quality biometric samples obtained on a laptop computer and authenticating them on lower quality biometric samples acquired with a mobile phone. To perform these experiments we develop three novel authentication protocols for the large publicly available MOBIO database. We evaluate state-of-the-art face, speaker and bi-modal authentication techniques and show that inter-session variability modelling using Gaussian mixture models provides a consistently robust system for face, speaker and bi-modal authentication. It is also shown that multi-algorithm fusion provides a consistent performance improvement for face, speaker and bi-modal authentication. Using this bi-modal multi-algorithm system we derive a state-of-the-art authentication system that obtains a half total error rate of 6.3% and 1.9% for Female and Male trials, respectively.

John Andrews : Architecture a Performing Art

The distinguished Australian architect surveys his career and examines how his architectural theories are expressed in his designs.

Curiosity driven reinforcement learning for motion planning on humanoids

Most previous work on artificial curiosity (AC) and intrinsic motivation focuses on basic concepts and theory. Experimental results are generally limited to toy scenarios, such as navigation in a simulated maze, or control of a simple mechanical system with one or two degrees of freedom. To study AC in a more realistic setting, we embody a curious agent in the complex iCub humanoid robot. Our novel reinforcement learning (RL) framework consists of a state-of-the-art, low-level, reactive control layer, which controls the iCub while respecting constraints, and a high-level curious agent, which explores the iCub's state-action space through information gain maximization, learning a world model from experience, controlling the actual iCub hardware in real-time. To the best of our knowledge, this is the first ever embodied, curious agent for real-time motion planning on a humanoid. We demonstrate that it can learn compact Markov models to represent large regions of the iCub's configuration space, and that the iCub explores intelligently, showing interest in its physical constraints as well as in objects it finds in its environment.

First Literacies: Art, Creativity, Play, Constructive Meaning-Making

In this chapter art and play are considered children’s ‘first languages’, and therefore are placed at the centre of a curriculum for young children. Through art and play, children represent thought and action, which underpins their later understanding of the ‘second languages’ of reading, writing and numbering. Key issues such as image-making, graphic action, imagination, narrative, empathetic engagement and internalised thought are analysed as evidence of children’s construction of knowledge through art and play. Symbol making is the essence of being human. In children’s art and play, their symbol use captures their sensory modes in emotional and embodied ways, as children know their worlds and their place. The chapter addresses how children’s creation, manipulation and meaning making through engaged interaction with art materials are precursors to learning to read and write and, as first languages, should not be discarded nor replaced. The notion of creativity is explored in relation to pedagogical approaches. In a climate of testing regimes that emphasise ‘academic’ achievements, teachers are encouraged to not lose sight of imagination, pretence, constructive meaning making, holistic teaching and being a co-player and co-artist.

Art and the anxious city: Public art, public interest and the public good

While public art is often considered a key hallmark of a creative city, artworks in the public realm also have the capacity to act as lightening rods for social anxiety at times of perceived crisis. This paper considers recent debates about government-sponsored public art projects in Queensland in light of three international case studies: Rodin’s Thinker in Paris, Tilted Arc in New York and Vault in Melbourne. It considers whether consensus positions on public art are possible or desirable in light of issues of spatial control, and proposes that well-negotiated anxieties about public art may be an indicator of creative vibrancy and dynamism that will assist in the future understanding of Queensland’s experiment with government-mandated public art.

A framework for identification of similarities between multiple algorithms

This thesis in software engineering presents a novel automated framework to identify similar operations utilized by multiple algorithms for solving related computing problems. It provides a new effective solution to perform multi-application based algorithm analysis, employing fundamentally light-weight static analysis techniques compared to the state-of-art approaches. Significant performance improvements are achieved across the objective algorithms through enhancing the efficiency of the identified similar operations, targeting discrete application domains.

"Rebirth: Combined art performance"--Shirin Madg & Sweet Sound Ensemble

Vanessa Mafe-Keane was invited to participate as choreographer in Iranian singer Shirin Madg 's project, Rebirth: Combined art performance. This project integrated singing, music, visual-art, film, dance and is based on the dissident poetry of female Iranian poet, Forough Farrokhzad. The choreographic dance movement focused on simple, lyrical, flowing classical dance forms that also incorporated everyday gestures and actions performed by two Queensland dancers, Caitlin MacKenzie and Abby Johnson. The choreographic intention was not to attempt to re-create Iranian dance practices instead, to draw inspiration and reference specific movement qualities. This was achieved through the subtle inclusion of spinning movements and focusing attention on the dancers’ arms and upper torso. This fusion became an underlying theme reflected throughout the choreographic component. Additionally, this project presented an opportunity to draw on past experiences and problem-solve ways to construct choreographic work where the dancers and the musical assemble group could be staged side by side. This experience highlighted differing approaches to rehearsal protocols within disciplines, the practicalities of staging different artists, understanding musical cues and the diversity of audience engagement. Performances: BEMAC Multicultural Centre, Brisbane 06 February 2015 and Helensvale Cultural Centre, Gold Coast 07 February 2015