FPGA implementation of an evolutionary algorithm for autonomous unmanned aerial vehicle on-board path planning

In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

A ‘service logic’ rationale for business model innovation

Successful firms use business model innovation to rethink the way they do business and transform industries. However, current research on business model innovation is lacking theoretical underpinnings and is in need of new insights. This objective of this paper is to advance our understanding of both the business model concept and business model innovation based on service logic as foundation for customer value and value creation. We present and discuss a rationale for business models based on ‘service logic’ with service as a value-supporting process and compared it with a business model based on ‘goods logic’ with goods as value-supporting resources. The implications for each of the business model dimensions: customer, value proposition, organizational architecture and revenue model, are described and discussed in detail.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

The primary school as a logic machine

This paper makes a case for thinking about the primary school as a logic machine (apparatus) as a way of thinking about processes of in-school stratification. Firstly we discuss related literature on in-school stratification in primary schools, particularly as it relates to literacy learning. Secondly we explain how school reform can be thought about in terms of the idea of the machine or apparatus. In which case the processes of in-school stratification can be mapped as more than simply concerns about school organisation (such as students grouping) but also involve a politics of truth, played out in each school, that constitutes school culture and what counts as ‘good’ pedagogy. Thirdly, the chapter will focus specifically on research conducted into primary schools in the Northern Suburbs of Adelaide, one of the most educationally disadvantaged regions in Australia, as a case study of the relationship between in-school stratification and the reproduction of inequality. We will draw from more than 20 years of ethnographic work in primary school in the northern suburbs of Adelaide and provide a snapshot of a recent attempt to improve literacy achievement in a few Northern Suburbs public primary schools (SILA project). The SILA project, through diagnostic reviews, has provided a significant analysis of the challenges facing policy and practice in such challenging school contexts that also maps onto existing (inter)national research. These diagnostic reviews said ‘hard things’ that required attention by SILA schools and these included: · an over reliance on whole class, low level, routine tasks and hence a lack of challenge and rigour in the learning tasks offered to students ; · a focus on the 'code breaking' function of language at the expense of richer conceptualisations of literacy that might guide teachers’ understanding of challenging pedagogies ; · the need for substantial shifts in the culture of schools, especially unsettling deficit views of students and their communities ; · a need to provide a more ‘consistent’ approach to teaching literacy across the school; · a need to focus School Improvement Plans in order to implement a clear focus on literacy learning; and, · a need to sustain professional learning to produce new knowledge and practice . The paper will conclude with suggestions for further research and possible reform projects into the primary school as a logic machine.

Comparison of high level FPGA hardware design for solving tri-diagonal linear systems

Reconfigurable computing devices can increase the performance of compute intensive algorithms by implementing application specific co-processor architectures. The power cost for this performance gain is often an order of magnitude less than that of modern CPUs and GPUs. Exploiting the potential of reconfigurable devices such as Field-Programmable Gate Arrays (FPGAs) is typically a complex and tedious hardware engineering task. Re- cently the major FPGA vendors (Altera, and Xilinx) have released their own high-level design tools, which have great potential for rapid development of FPGA based custom accelerators. In this paper, we will evaluate Altera’s OpenCL Software Development Kit, and Xilinx’s Vivado High Level Sythesis tool. These tools will be compared for their per- formance, logic utilisation, and ease of development for the test case of a Tri-diagonal linear system solver.

Bit-stream-based space vector modulators

Bit-stream-based control, which uses one bit wide signals to control power electronics applications, is a new approach for controller design in power electronic systems. This study presents a novel family of three-phase space vector modulators, which are based on the bit-stream technique and suitable for three-phase inverter systems. Each of the proposed modulators simultaneously converts a two-phase reference to the three-phase domain and reduces switching frequencies to reasonable levels. The modulators do not require carrier oscillators, trigonometric functions or, in some cases, sector detectors. A complete three-phase modulator can be implemented in as few as 102 logic elements. The performance of the proposed modulators is compared through simulation and experimental testing of a 6 kW, three-phase DC-to-AC inverter. Subject to limits on the modulation index, the proposed modulators deliver spread-spectrum output currents with total harmonic distortion comparable to a standard carrier-based space vector pulse width modulator.

Logic-gate devices based on printed polymer semiconducting nanostripes

The applications of organic semiconductors in complex circuitry such as printed CMOS-like logic circuits demand miniaturization of the active structures to the submicrometric and nanoscale level while enhancing or at least preserving the charge transport properties upon processing. Here, we addressed this issue by using a wet lithographic technique, which exploits and enhances the molecular order in polymers by spatial confinement, to fabricate ambipolar organic field effect transistors and inverter circuits based on nanostructured single component ambipolar polymeric semiconductor. In our devices, the current flows through a precisely defined array of nanostripes made of a highly ordered diketopyrrolopyrrole-benzothiadiazole copolymer with high charge carrier mobility (1.45 cm2 V-1 s-1 for electrons and 0.70 cm2 V-1 s-1 for holes). Finally, we demonstrated the functionality of the ambipolar nanostripe transistors by assembling them into an inverter circuit that exhibits a gain (105) comparable to inverters based on single crystal semiconductors.

Purposeful program theory: Effective use of theories of change and logic models [Book Review]

The purpose of this book by two Australian authors is to: introduce the audience to the full complement of contextual elements found within program theory; offer practical suggestions to engage with theories of change, theories of action and logic models; and provide substantial evidence for this approach through scholarly literature, practice case studies together with the authors' combined experience of 60 years.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

Fuzzy logic to evaluate driving maneuvers: An integrated approach to improve training

Driver training is one of the interventions aimed at mitigating the number of crashes that involve novice drivers. Our failure to understand what is really important for learners, in terms of risky driving, is one of the many drawbacks restraining us to build better training programs. Currently, there is a need to develop and evaluate Advanced Driving Assistance Systems that could comprehensively assess driving competencies. The aim of this paper is to present a novel Intelligent Driver Training System (IDTS) that analyses crash risks for a given driving situation, providing avenues for improvement and personalisation of driver training programs. The analysis takes into account numerous variables acquired synchronously from the Driver, the Vehicle and the Environment (DVE). The system then segments out the manoeuvres within a drive. This paper further presents the usage of fuzzy set theory to develop the safety inference rules for each manoeuvre executed during the drive. This paper presents a framework and its associated prototype that can be used to comprehensively view and assess complex driving manoeuvres and then provide a comprehensive analysis of the drive used to give feedback to novice drivers.