Open source computer-vision based guidance system for UAVs on-board decision making

The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

Digital competence and professional development of vocational education and training teachers in Queensland

Teaching with digital technologies is essential to the development of 21st century students’ graduate capabilities. However, relatively little is known about the extent to which Queensland VET teachers engage with digitally-enhanced teaching, or have the capacity to do so. Using a mixed methods approach, this thesis investigated the current digital teaching capacities of VET teachers and how current professional development opportunities are helping to address their learning needs.

Promoting and providing expert guidance in work-intensive clinical settings

This paper discusses how expert guidance can be best provided in work intensive clinical settings. The adequacy for supporting learning in the clinical practicum for health care disciplines is often complicated by the intensive work practices in healthcare settings. Often, clinicians' work is so intense that the scope for providing close guidance for students is quite restricted. The case advanced here draws on a range of empirical work to propose how clinician-student interactions might be optimized through the provision of a clinical ccn guided learning such as demonstrating and role-modeling. These roles can contribute in essential ways to the development of learning environments where clinicians have the opportunity to facilitate the learning of others as part of their workload, and without being burdened by the requirements of teaching and assessment processes. It differs from other approaches because although clinicians partner students and provide feedback to them, clinicians are not expected to formally assess or award a grade for student performance. Assessment and remedial action, when required, is undertaken by the role of a designated clinical supervisor qualified to perform such activities. © 2010 Springer Science+Business Media B.V.