Deficiencies of scope statements in ITLET standardization

To execute good design one not only needs to know what to do and how to do it, but also why it should be done. For a standardization expert the rationale of a standardization project may be found in the proposal for a new work item or terms of reference, but rarely in the scope statement. However, it is also commonplace that the rationale of the project is not clearly stated in any of these parts. If the rationale is not surfaced in the early phases of a project, it is left to the design, sense-making and negotiation cycles of the design process to orient the project towards a goal. This paper explores how scope statements are used to position standardization projects in the IT for Learning, Education and Training (ITLET) domain, and how scope and rationale are understood in recent projects in European and international standardization. Based on two case-studies the paper suggests some actions for further research and improvement of the process.

Creating synergy in teacher education through robotics-based STEM activities

Robotics has created opportunities for educators to teach concepts across Science, Technology, Engineering, and Mathematics (STEM). This is one of the reasons robotics is becoming increasingly common in primary and secondary classrooms in Australia. To enable pre-service teachers to design engaging STEM activities that incorporate these technologies, robotics is part of the teaching program in the primary education degree at Queensland University of Technology (QUT). A number of pre-service teachers also choose to extend their abilities by implementing robotics activities on field studies, in schools on a voluntary basis, and in outreach activities such as the Robotics@QUT project. The Robotics@QUT project is a support network developed to build professional knowledge and capacity of classroom teachers in schools from a low SES area, engaging in robotics-based STEM activities. Professional Development (PD) workshops are provided to teachers in order to build their knowledge and confidence in implementing robotics activities in their classrooms, loan kits are provided, and pre-service teacher visits arranged to provide the teachers with on-going support. A key feature of the project is the partnerships developed between the teachers and the pre-service teachers involved in the project. The purpose of this study was to ascertain how the teachers in the project perceived the value of the PD workshops and the pre-service teachers’ involvement and what the benefits of the involvement in the project were for the pre-service teachers. Seventeen teachers completed a five-point (1-5) likert scale questionnaire regarding their involvement in the Robotics@QUT project. Teachers’ responses on the value of the project and the pre-service teacher support highlighted the benefits of the partnerships formed and provided insights into the value of the support provided by the pre-service teachers. This paper also describes one pre-service teacher’s experience with the project and the perceived benefits from being involved.

Engaging students (and their teachers) in STEM through robotics

Robotics@QUT is a university outreach program aimed at building pre- and in-service teacher capacity to encourage interest in Science, Technology, Engineering and Mathematics (STEM) subjects with school children from low socio-economic status areas. Currently over 35 schools are involved in the outreach program. Professional Development workshops are provided to teachers to build their knowledge in implementing robotics-based STEM activities in their classrooms, robotics loan kits are provided, and pre-service teacher visits arranged to provide the teachers with on-going support. The program also provides opportunities for school students to engage in robotics-based on-campus activities and competitions and is seen as a way to build aspirations for university. This paper presents an interim evaluation that examines the value of the Robotics@QUT program for the teachers, pre-service teachers and school students participating in the program. Surveys were administered to determine the participants’ perceived benefits of being involved and their perceptions of the program. The data gathered from the teachers showed that they had gained knowledge and confidence and felt that the Robotics@QUT program had assisted them to deliver engaging robotics-based STEM activities in their classrooms. The pre-service teachers’ responses focused on benefits for themselves, for their future teaching careers and for the school students involved. The school students’ responses focused on their increased knowledge and confidence to pursue future STEM studies and careers.

Towards a framework for business process standardization

Organizations increasingly seek to achieve operational excellence by standardizing business processes. Standardization initiatives may have different purposes, such as process streamlining, process automation, or even process outsourcing. However, standardization of processes is easier said than done. Standardization success depends on various factors, such as existent IT capabilities, available standard frameworks, market situation, and the processes’ nature, such as their level of routine or structuredness. This paper uncovers the complex nature and relative influence of process-internal and -environmental factors relevant to process standardization, by discussing three case studies from different industries. The findings are summarized in a set of initial conjectures about successful process standardization. This exploratory research is a first step towards uncovering the characteristics of successful process standardization efforts.

Lego robotics : an authentic problem solving tool?

With the current curriculum focus on correlating classroom problem solving lessons to real-world contexts, are LEGO robotics an effective problem solving tool? This present study was designed to investigate this question and to ascertain what problem solving strategies primary students engaged with when working with LEGO robotics and whether the students were able to effectively relate their problem solving strategies to real-world contexts. The qualitative study involved 23 Grade 6 students participating in robotics activities. The study included data collected from researcher observations of student problem solving discussions, collected software programs, and data from a student completed questionnaire. Results from the study indicated that the robotic activities assisted students to reflect on the problem-solving decisions they made. The study also highlighted that the students were able to relate their problem solving strategies to real-world contexts. The study demonstrated that while LEGO robotics can be considered useful problem solving tools in the classroom, careful teacher scaffolding needs to be implemented in regards to correlating LEGO with authentic problem solving. Further research in regards to how teachers can best embed real-world contexts into effective robotics lessons is recommended.

LEGO robotics : an authentic problem solving tool?

With the current curriculum focus on correlating classroom problem solving lessons to real-world contexts, are LEGO robotics an effective problem solving tool? This present study was designed to investigate this question and to ascertain what problem solving strategies primary students engaged with when working with LEGO robotics and whether the students were able to effectively relate their problem solving strategies to real-world contexts. The qualitative study involved 23 Grade 6 students participating in robotics activities at a Brisbane primary school. The study included data collected from researcher observations of student problem solving discussions, collected software programs, and data from a student completed questionnaire. Results from the study indicated that the robotic activities assisted students to reflect on the problem solving decisions they made. The study also highlighted that the students were able to relate their problem solving strategies to real-world contexts. The study demonstrated that while LEGO robotics can be considered useful problem solving tools in the classroom, careful teacher scaffolding needs to be implemented in regards to correlating LEGO with authentic problem solving. Further research in regards to how teachers can best embed realworld contexts into effective robotics lessons is recommended.

Image based visual servo control for fixed wing UAVs tracking linear infrastructure in wind

This paper presents an Image Based Visual Servo control design for Fixed Wing Unmanned Aerial Vehicles tracking locally linear infrastructure in the presence of wind using a body fixed imaging sensor. Visual servoing offers improved data collection by posing the tracking task as one of controlling a feature as viewed by the inspection sensor, although is complicated by the introduction of wind as aircraft heading and course angle no longer align. In this work it is shown that the effects of wind alter the desired line angle required for continuous tracking to equal the wind correction angle as would be calculated to set a desired course. A control solution is then sort by linearizing the interaction matrix about the new feature pose such that kinematics of the feature can be augmented with the lateral dynamics of the aircraft, from which a state feedback control design is developed. Simulation results are presented comparing no compensation, integral control and the proposed controller using the wind correction angle, followed by an assessment of response to atmospheric disturbances in the form of turbulence and wind gusts

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Datasets for the evaluation of multi-sensor perception in natural environments with challenging conditions

This paper presents large, accurately calibrated and time-synchronised datasets, gathered outdoors in controlled environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. It discusses how the data collection process was designed, the conditions in which these datasets have been gathered, and some possible outcomes of their exploitation, in particular for the evaluation of performance of sensors and perception algorithms for UGVs.

A collaborative robotics engagement project

This paper reports on an evaluation of a collaborative robotics engagement project involving teachers from local schools and an academic from Queensland University of Technology (QUT). Engaged community projects are aimed at building stronger relationships between universities and their local communities (Sandman, Williams & Abrams, 2009). This partnership leads to mutually beneficial outcomes, builds community capacity, and can focus on aspirations and access to higher education for school students (Scull & Cuthill, 2010). The Robotics@QUT project aimed to build a partnership between local teachers and the university in order to provide students from a low SES area opportunity to engage in robotics-based Science, Technology, Engineering, and Mathematics (STEM) activities. Students from low SES regions are underrepresented at university and less likely to pursue studies in these fields (Bradley, Noonan, Nugent, & Scales, 2008). Having teachers who provide engaging STEM activities is an important motivating factor for students to enjoy STEM and do well in STEM subjects (Tytler, Osborne Williams Tytler & Clark, 2008).

Long-term experiments with an adaptive spherical view representation for navigation in changing environments

Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In this work, we introduce a method to update the reference views in a hybrid metrictopological map so that a mobile robot can continue to localize itself in a changing environment. The updating mechanism, based on the multi-store model of human memory, incorporates a spherical metric representation of the observed visual features for each node in the map, which enables the robot to estimate its heading and navigate using multi-view geometry, as well as representing the local 3D geometry of the environment. A series of experiments demonstrate the persistence performance of the proposed system in real changing environments, including analysis of the long-term stability.

Principles of goal-directed spatial robot navigation in biomimetic models

Mobile robots and animals alike must effectively navigate their environments in order to achieve their goals. For animals goal-directed navigation facilitates finding food, seeking shelter or migration; similarly robots perform goal-directed navigation to find a charging station, get out of the rain or guide a person to a destination. This similarity in tasks extends to the environment as well; increasingly, mobile robots are operating in the same underwater, ground and aerial environments that animals do. Yet despite these similarities, goal-directed navigation research in robotics and biology has proceeded largely in parallel, linked only by a small amount of interdisciplinary research spanning both areas. Most state-of-the-art robotic navigation systems employ a range of sensors, world representations and navigation algorithms that seem far removed from what we know of how animals navigate; their navigation systems are shaped by key principles of navigation in ‘real-world’ environments including dealing with uncertainty in sensing, landmark observation and world modelling. By contrast, biomimetic animal navigation models produce plausible animal navigation behaviour in a range of laboratory experimental navigation paradigms, typically without addressing many of these robotic navigation principles. In this paper, we attempt to link robotics and biology by reviewing the current state of the art in conventional and biomimetic goal-directed navigation models, focusing on the key principles of goal-oriented robotic navigation and the extent to which these principles have been adapted by biomimetic navigation models and why.

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.