The architecture of children’s use of language and tools when problem solving collaboratively with robotics

This paper demonstrates, following Vygotsky, that language and tool use has a critical role in the collaborative problem-solving behaviour of school-age children. It reports original ethnographic classroom research examining the convergence of speech and practical activity in children’s collaborative problem solving with robotics programming tasks. The researchers analysed children’s interactions during a series of problem solving experiments in which Lego Mindstorms toolsets were used by teachers to create robotics design challenges among 24 students in a Year 4 Australian classroom (students aged 8.5–9.5 years). The design challenges were incrementally difficult, beginning with basic programming of straight line movement, and progressing to more complex challenges involving programming of the robots to raise Lego figures from conduit pipes using robots as pulleys with string and recycled materials. Data collection involved micro-genetic analysis of students’ speech interactions with tools, peers, and other experts, teacher interviews, and student focus group data. Coding the repeated patterns in the transcripts, the authors outline the structure of the children’s social speech in joint problem solving, demonstrating the patterns of speech and interaction that play an important role in the socialisation of the school-age child’s practical intellect.

Low cost localisation for agricultural robotics

This paper presents a pose estimation approach that is resilient to typical sensor failure and suitable for low cost agricultural robots. Guiding large agricultural machinery with highly accurate GPS/INS systems has become standard practice, however these systems are inappropriate for smaller, lower-cost robots. Our positioning system estimates pose by fusing data from a low-cost global positioning sensor, low-cost inertial sensors and a new technique for vision-based row tracking. The results first demonstrate that our positioning system will accurately guide a robot to perform a coverage task across a 6 hectare field. The results then demonstrate that our vision-based row tracking algorithm improves the performance of the positioning system despite long periods of precision correction signal dropout and intermittent dropouts of the entire GPS sensor.

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.

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.

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).

Robotics for sustainable broad-acre agriculture

This paper describes the development of small low-cost cooperative robots for sustainable broad-acre agriculture to increase broad-acre crop production and reduce environmental impact. The current focus of the project is to use robotics to deal with resistant weeds, a critical problem for Australian farmers. To keep the overall system affordable our robot uses low-cost cameras and positioning sensors to perform a large scale coverage task while also avoiding obstacles. A multi-robot coordinator assigns parts of a given field to individual robots. The paper describes the modification of an electric vehicle for autonomy and experimental results from one real robot and twelve simulated robots working in coordination for approximately two hours on a 55 hectare field in Emerald Australia. Over this time the real robot 'sprayed' 6 hectares missing 2.6% and overlapping 9.7% within its assigned field partition, and successfully avoided three obstacles.

Fast re-parameterisation of Gaussian mixture models for robotics applications

Autonomous navigation and picture compilation tasks require robust feature descriptions or models. Given the non Gaussian nature of sensor observations, it will be shown that Gaussian mixture models provide a general probabilistic representation allowing analytical solutions to the update and prediction operations in the general Bayesian filtering problem. Each operation in the Bayesian filter for Gaussian mixture models multiplicatively increases the number of parameters in the representation leading to the need for a re-parameterisation step. A computationally efficient re-parameterisation step will be demonstrated resulting in a compact and accurate estimate of the true distribution.

Text recognition approaches for indoor robotics : a comparison

This paper evaluates the performance of different text recognition techniques for a mobile robot in an indoor (university campus) environment. We compared four different methods: our own approach using existing text detection methods (Minimally Stable Extremal Regions detector and Stroke Width Transform) combined with a convolutional neural network, two modes of the open source program Tesseract, and the experimental mobile app Google Goggles. The results show that a convolutional neural network combined with the Stroke Width Transform gives the best performance in correctly matched text on images with single characters whereas Google Goggles gives the best performance on images with multiple words. The dataset used for this work is released as well.

Robotics for the mining industry

The mining industry is highly suitable for the application of robotics and automation technology since the work is both arduous and dangerous. However, while the industry makes extensive use of mechanisation it has shown a slow uptake of automation. A major cause of this is the complexity of the task, and the limitations of existing automation technology which is predicated on a structured and time invariant working environment. Here we discuss the topic of mining automation from a robotics and computer vision perspective — as a problem in sensor based robot control, an issue which the robotics community has been studying for nearly two decades. We then describe two of our current mining automation projects to demonstrate what is possible for both open-pit and underground mining operations.

A real-time software architecture for robotics and automation

This paper describes a software architecture for real-world robotic applications. We discuss issues of software reliability, testing and realistic off-line simulation that allows the majority of the automation system to be tested off-line in the laboratory before deployment in the field. A recent project, the automation of a very large mining machine is used to illustrate the discussion.

3D perception for mining robotics

This paper discusses some of the sensing technologies available for guiding robot manipulators for a class of underground mining tasks including drilling jumbos, bolting arms, shotcreters or explosive chargers. Data acquired with such sensors, in the laboratory and underground, is presented.

Developing students’ technological literacy through robotics activities

One way to consider Technology as other than an add-on might be to consider the opportunities to learn literacies opened by participation in technology. In this commentary Vinesh Chandra considers this in light of robotics lessons with primary school students as part of his work in the UR Learning project.

Embodying a future for the future: Creative Robotics and Ecosophical Practice

In recent years I have begun to integrate Creative Robotics into my Ecosophically-led art practices – which I have long deployed to investigate, materialise and engage thorny, ecological questions of the Anthropocene, seeking to understand how such forms of practice may promote the cultural conditions required to assure, rather than degrade, our collective futures. Many of us would instinctively conceive of robotics as an industrially driven endeavor, shaped by the pursuit of relentless efficiencies. Instead I ask through my practices, might the nascent field of Creative Robotics still be able to emerge with radically different frames of intention? Might creative practitioners still be able to shape experiences using robotic media that retain a healthy criticality towards such productivist lineages? Could this nascent form even bring forward fresh new techniques and assemblages that better encourage conversations around sustaining a future for the future, and, if so, which of its characteristics presents the greatest opportunities? I therefore ask, when Creative Robotics and Ecosophical Practice combine forces in strategic intervention, what qualities of this hybrid might best further the central aims of Ecosophical Practice – encouraging cultural conditions required to assure a future for the future?

Field and Service Robotics: Results of the 9th International Conference

The Field and Service Robotics (FSR) conference is a single track conference with a specific focus on field and service applications of robotics technology. The goal of FSR is to report and encourage the development of field and service robotics. These are non-factory robots, typically mobile, that must operate in complex and dynamic environments. Typical field robotics applications include mining, agriculture, building and construction, forestry, cargo handling and so on. Field robots may operate on the ground (of Earth or planets), under the ground, underwater, in the air or in space. Service robots are those that work closely with humans, importantly the elderly and sick, to help them with their lives. The first FSR conference was held in Canberra, Australia, in 1997. Since then the meeting has been held every 2 years in Asia, America, Europe and Australia. It has been held in Canberra, Australia (1997), Pittsburgh, USA (1999), Helsinki, Finland (2001), Mount Fuji, Japan (2003), Port Douglas, Australia (2005), Chamonix, France (2007), Cambridge, USA (2009), Sendai, Japan (2012) and most recently in Brisbane, Australia (2013). This year we had 54 submissions of which 36 were selected for oral presentation. The organisers would like to thank the international committee for their invaluable contribution in the review process ensuring the overall quality of contributions. The organising committee would also like to thank Ben Upcroft, Felipe Gonzalez and Aaron McFadyen for helping with the organisation and proceedings. and proceedings. The conference was sponsored by the Australian Robotics and Automation Association (ARAA), CSIRO, Queensland University of Technology (QUT), Defence Science and Technology Organisation Australia (DSTO) and the Rio Tinto Centre for Mine Automation, University of Sydney.

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.