“I have to rest all the time because you are not allowed to play”: Exploring children’s perceptions of autonomy during sleep-time in long day care services

Daytime sleep is a significant part of the daily routine for children attending early childhood education and care (ECEC) services in Australia and many other countries. The practice of sleep-time can account for a substantial portion of the day in ECEC and often involves a mandated sleep/rest period for all children, including older preschool-aged children. Yet, there is evidence that children have a reduced need for daytime sleep as they approach school entry age and that continuation of mandated sleep-time in ECEC for preschool-aged children may have a negative impact on their health, development, learning and well-being. Mandated sleep-time practices also go against current quality expectations for services to support children’s agency and autonomy in ECEC. This study documents children’s reports of their experiences of sleep-time in ECEC. Semi-structured interviews were conducted with 54 preschool-aged children (44–63 months) across four long day ECEC services that employed a range of sleep-time practices. Findings provide a snapshot of children’s views and experiences of sleep-time and perceptions of autonomy-supportive practices. These provide a unique platform to support critical reflection on sleep-time policies and practices, with a view to continuous quality improvement in ECEC. This study forms part of a programme of work from the Sleep in Early Childhood research group. Our work examines sleep practices in ECEC, the subsequent staff, parent and child experiences and impacts on family and child learning and development outcomes.

A critical evaluation of literature on robot path planning in dynamic environment

Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.

From vision to actions: Towards adaptive and autonomous humanoid robots

Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

Ship Seakeeping Operability, Motion Control, and Autonomy - A Bayesian Perspective

Ship seakeeping operability refers to the quantification of motion performance in waves relative to mission requirements. This is used to make decisions about preferred vessel designs, but it can also be used as comprehensive assessment of the benefits of ship-motion-control systems. Traditionally, operability computation aggregates statistics of motion computed over over the envelope of likely environmental conditions in order to determine a coefficient in the range from 0 to 1 called operability. When used for assessment of motion-control systems, the increase of operability is taken as the key performance indicator. The operability coefficient is often given the interpretation of the percentage of time operable. This paper considers an alternative probabilistic approach to this traditional computation of operability. It characterises operability not as a number to which a frequency interpretation is attached, but as a hypothesis that a vessel will attain the desired performance in one mission considering the envelope of likely operational conditions. This enables the use of Bayesian theory to compute the probability of that this hypothesis is true conditional on data from simulations. Thus, the metric considered is the probability of operability. This formulation not only adheres to recent developments in reliability and risk analysis, but also allows incorporating into the analysis more accurate descriptions of ship-motion-control systems since the analysis is not limited to linear ship responses in the frequency domain. The paper also discusses an extension of the approach to the case of assessment of increased levels of autonomy for unmanned marine craft.

The dynamics of individual teacher autonomy: A case study of teachers' work in a Queensland secondary school

The emphasis on collegiality and collaboration in the literature on teachers' work and school reform has tended to underplay the significance of teacher autonomy. This thesis explores the dynamics of teachers' understandings and experiences of individual teacher autonomy (as contrasted with collective autonomy) in an independent school in Queensland which promoted itself as a 'teachers' school' with a strong commitment to individual teacher autonomy. The research was a case study which drew on methodological signposts from critical, feminist and traditional ethnography. Intensive fieldwork in the school over five months incorporated the ethnographic techniques of observation, interviews and document analysis. Teachers at Thornton College understood their experience of individual autonomy at three interrelated levels--in terms of their work in the classroom, their working life in the school, and their voice in the decision-making processes of the school. They felt that they experienced a great deal of individual autonomy at each of these three levels. These understandings and experiences of autonomy were encumbered or enabled by a range of internal and external stakeholder groups. There were also a number of structural influences (community perceptions, market forces, school size, time and bureaucracy) emerging from the economic, social and political structures in Australian society which influenced the experience of autonomy by teachers. The experience of individual teacher autonomy was constantly shifting, but there were some emergent patterns. Consensus on educational goals and vision, and strong expressions of trust and respect between teachers and stakeholders in the school, characterised the contexts in which teachers felt they experienced high levels of autonomy in their work. The demand for accountability and desire for relatedness motivated stakeholders and structural forces to influence teacher autonomy. Some significant gaps emerged between the rhetoric of a commitment to individual teacher autonomy and decision-making practices in the school, that gave ultimate power to the co-principals. Despite the rhetoric and promotion of non-hierarchical structures and collaborative decision-making processes, many teachers perceived that their experience of individual autonomy remained subject to the exercise of 'partial democracy' by school leaders.

My robot Valentine: Could you fall in love with a robot?

Imagine it’s Valentine’s Day and you’re sitting in a restaurant across the table from your significant other, about to start a romantic dinner. As you gaze into each other’s eyes, you wonder how it can possibly be true that as well as not eating, your sweetheart does not – cannot – love you. Impossible, you think, as you squeeze its synthetic hand...

Place categorization and semantic mapping on a mobile robot

In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.

Cooperation using a robotic ad hoc network made from Bluetooth, JXTA, OSGi and other commercial off the shelf (COTS) products

Abstract - Mobile devices in the near future will need to collaborate to fulfill their function. Collaboration will be done by communication. We use a real world example of robotic soccer to come up with the necessary structures required for robotic communication. A review of related work is done and it is found no examples come close to providing a RANET. The robotic ad hoc network (RANET) we suggest uses existing structures pulled from the areas of wireless networks, peer to peer and software life-cycle management. Gaps are found in the existing structures so we describe how to extend some structures to satisfy the design. The RANET design supports robot cooperation by exchanging messages, discovering needed skills that other robots on the network may possess and the transfer of these skills. The network is built on top of a Bluetooth wireless network and uses JXTA to communicate and transfer skills. OSGi bundles form the skills that can be transferred. To test the nal design a reference implementation is done. Deficiencies in some third party software is found, specifically JXTA and JamVM and GNU Classpath. Lastly we look at how to fix the deciencies by porting the JXTA C implementation to the target robotic platform and potentially eliminating the TCP/IP layer, using UDP instead of TCP or using an adaptive TCP/IP stack. We also propose a future areas of investigation; how to seed the configuration for the Personal area network (PAN) Bluetooth protocol extension so a Bluetooth TCP/IP link is more quickly formed and using the STP to allow multi-hop messaging and transfer of skills.

Mapping of indoor environments by robots using low-cost vision sensors

For robots to operate in human environments they must be able to make their own maps because it is unrealistic to expect a user to enter a map into the robot’s memory; existing floorplans are often incorrect; and human environments tend to change. Traditionally robots have used sonar, infra-red or laser range finders to perform the mapping task. Digital cameras have become very cheap in recent years and they have opened up new possibilities as a sensor for robot perception. Any robot that must interact with humans can reasonably be expected to have a camera for tasks such as face recognition, so it makes sense to also use the camera for navigation. Cameras have advantages over other sensors such as colour information (not available with any other sensor), better immunity to noise (compared to sonar), and not being restricted to operating in a plane (like laser range finders). However, there are disadvantages too, with the principal one being the effect of perspective. This research investigated ways to use a single colour camera as a range sensor to guide an autonomous robot and allow it to build a map of its environment, a process referred to as Simultaneous Localization and Mapping (SLAM). An experimental system was built using a robot controlled via a wireless network connection. Using the on-board camera as the only sensor, the robot successfully explored and mapped indoor office environments. The quality of the resulting maps is comparable to those that have been reported in the literature for sonar or infra-red sensors. Although the maps are not as accurate as ones created with a laser range finder, the solution using a camera is significantly cheaper and is more appropriate for toys and early domestic robots.

On medium specificity and discipline crossovers in modern art : An interview with Jacques Ranciére on Medium-Specificity and Discipline Crossovers in Modern Art

Jacques Ranciere's work on aesthetics has received a great deal of attention recently. Given his work has enormous range – taking in art and literature, political theory, historiography, pedagogy and worker's history – Andrew McNamara and Toni Ross (UNSW) seek to explore his wider project in this interview, while showing how it leads to his alternative insights into aesthetics. Rancière sets aside the core suppositions linking the medium to aesthetic judgment, which has informed many definitions of modernism. Rancière is emphatic in freeing aesthetic judgment from issues of medium-specificity. He argues that the idea of autonomy associated with medium-specificity – or 'truth to the medium' – was 'a very late one' in modernism, and that post-medium trends were already evident in early modernism. While not stressing a simple continuity between early modernism and contemporary art, Ranciere nonetheless emphasizes the ethical and political ramifications of maintaining an a-disciplinary stance.

Topological SLAM Using Fast Vision Techniques

In this paper we propose a method for vision only topological simultaneous localisation and mapping (SLAM). Our approach does not use motion or odometric information but a sequence of colour histograms from visited places. In particular, we address the perceptual aliasing problem which occurs using external observations only in topological navigation. We propose a Bayesian inference method to incrementally build a topological map by inferring spatial relations from the sequence of observations while simultaneously estimating the robot's location. The algorithm aims to build a small map which is consistent with local adjacency information extracted from the sequence measurements. Local adjacency information is incorporated to disambiguate places which otherwise would appear to be the same. Experiments in an indoor environment show that the proposed technique is capable of dealing with perceptual aliasing using visual observations only and successfully performs topological SLAM.

Topological SLAM using neighbourhood information of places

Perceptual aliasing makes topological navigation a difficult task. In this paper we present a general approach for topological SLAM~(simultaneous localisation and mapping) which does not require motion or odometry information but only a sequence of noisy measurements from visited places. We propose a particle filtering technique for topological SLAM which relies on a method for disambiguating places which appear indistinguishable using neighbourhood information extracted from the sequence of observations. The algorithm aims to induce a small topological map which is consistent with the observations and simultaneously estimate the location of the robot. The proposed approach is evaluated using a data set of sonar measurements from an indoor environment which contains several similar places. It is demonstrated that our approach is capable of dealing with severe ambiguities and, and that it infers a small map in terms of vertices which is consistent with the sequence of observations.

Situational factors and entrepreneurial intentions

Entrepreneurship can provide a satisfying and rewarding working life, providing a flexible lifestyle and considerable business autonomy. It is becoming an increasingly important career option for school and university graduates.