Visual servoing of a car-like vehicle - an application of omnidirectional vision

In this paper, we develop the switching controller presented by Lee et al. for the pose control of a car-like vehicle, to allow the use of an omnidirectional vision sensor. To this end we incorporate an extension to a hypothesis on the navigation behaviour of the desert ant, cataglyphis bicolor, which leads to a correspondence free landmark based vision technique. The method we present allows positioning to a learnt location based on feature bearing angle and range discrepancies between the robot's current view of the environment, and that at a learnt location. We present simulations and experimental results, the latter obtained using our outdoor mobile platform.

Low-cost flight control system for a small autonomous helicopter

In this paper we describe a low-cost flight control system for a small (60 class) helicopter which is part of a larger project to develop an autonomous flying vehicle. Our approach differs from that of others in not using an expensive inertial/GPS sensing system. The primary sensors for vehicle stabilization are a low-cost inertial sensor and a pair of CMOS cameras. We describe the architecture of our flight control system, the inertial and visual sensing subsystems and present some flight control results.

Experimental evaluation of position control methods for hydraulic systems

Presents a unified and systematic assessment of ten position control strategies for a hydraulic servo system with single-ended cylinder driven by a proportional directional control valve. We aim at identifying those methods that achieve better tracking, have a low sensitivity to system uncertainties, and offer a good balance between development effort and end results. A formal approach for solving this problem relies on several practical metrics, which is introduced herein. Their choice is important, as the comparison results between controllers can vary significantly, depending on the selected criterion. Apart from the quantitative assessment, we also raise aspects which are difficult to quantify, but which must stay in attention when considering the position control problem for this class of hydraulic servo systems.

The Application of wireless LANS in mine automation

The objective of this paper is to provide an overview of mine automation applications, developed at the Queensland Centre for Advanced Technology (QCAT), which make use of IEEE 802.11b wireless local area networks (WLANs). The paper has been prepared for a 2002 conference entitled "Creating the Virtual Enterprise - Leveraging wireless technology within existing business models for corporate advantage". Descriptions of the WLAN components have been omitted here as such details are presented in the accompanying papers. The structure of the paper is as follows. Application overviews are provided in Sections 2 to 7. Some pertinent strengths and weaknesses are summarised in Section 8. Please refer to http://www.mining-automation.com/ or contact the authors for further information.

Flying-capacitor-based chopper circuit for DC capacitor voltage balancing in diode-clamped multilevel inverter

This paper proposes a flying-capacitor-based chopper circuit for dc capacitor voltage equalization in diode-clamped multilevel inverters. Its important features are reduced voltage stress across the chopper switches, possible reduction in the chopper switching frequency, improved reliability, and ride-through capability enhancement. This topology is analyzed using three- and four-level flying-capacitor-based chopper circuit configurations. These configurations are different in capacitor and semiconductor device count and correspondingly reduce the device voltage stresses by half and one-third, respectively. The detailed working principles and control schemes for these circuits are presented. It is shown that, by preferentially selecting the available chopper switch states, the dc-link capacitor voltages can be efficiently equalized in addition to having tightly regulated flying-capacitor voltages around their references. The various operating modes of the chopper are described along with their preferential selection logic to achieve the desired performances. The performance of the proposed chopper and corresponding control schemes are confirmed through both simulation and experimental investigations.

Clustered blind beamforming from ad-hoc microphone arrays

Microphone arrays have been used in various applications to capture conversations, such as in meetings and teleconferences. In many cases, the microphone and likely source locations are known \emph{a priori}, and calculating beamforming filters is therefore straightforward. In ad-hoc situations, however, when the microphones have not been systematically positioned, this information is not available and beamforming must be achieved blindly. In achieving this, a commonly neglected issue is whether it is optimal to use all of the available microphones, or only an advantageous subset of these. This paper commences by reviewing different approaches to blind beamforming, characterising them by the way they estimate the signal propagation vector and the spatial coherence of noise in the absence of prior knowledge of microphone and speaker locations. Following this, a novel clustered approach to blind beamforming is motivated and developed. Without using any prior geometrical information, microphones are first grouped into localised clusters, which are then ranked according to their relative distance from a speaker. Beamforming is then performed using either the closest microphone cluster, or a weighted combination of clusters. The clustered algorithms are compared to the full set of microphones in experiments on a database recorded on different ad-hoc array geometries. These experiments evaluate the methods in terms of signal enhancement as well as performance on a large vocabulary speech recognition task.

Optimising figure of merit for phonetic spoken term detection

This paper introduces a novel technique to directly optimise the Figure of Merit (FOM) for phonetic spoken term detection. The FOM is a popular measure of sTD accuracy, making it an ideal candiate for use as an objective function. A simple linear model is introduced to transform the phone log-posterior probabilities output by a phe classifier to produce enhanced log-posterior features that are more suitable for the STD task. Direct optimisation of the FOM is then performed by training the parameters of this model using a non-linear gradient descent algorithm. Substantial FOM improvements of 11% relative are achieved on held-out evaluation data, demonstrating the generalisability of the approach.

Accurate silhouettes for surveillance : improved motion segmentation using graph cuts

Silhouettes are common features used by many applications in computer vision. For many of these algorithms to perform optimally, accurately segmenting the objects of interest from the background to extract the silhouettes is essential. Motion segmentation is a popular technique to segment moving objects from the background, however such algorithms can be prone to poor segmentation, particularly in noisy or low contrast conditions. In this paper, the work of [3] combining motion detection with graph cuts, is extended into two novel implementations that aim to allow greater uncertainty in the output of the motion segmentation, providing a less restricted input to the graph cut algorithm. The proposed algorithms are evaluated on a portion of the ETISEO dataset using hand segmented ground truth data, and an improvement in performance over the motion segmentation alone and the baseline system of [3] is shown.

Multi-modal object tracking using dynamic performance metrics

Intelligent surveillance systems typically use a single visual spectrum modality for their input. These systems work well in controlled conditions, but often fail when lighting is poor, or environmental effects such as shadows, dust or smoke are present. Thermal spectrum imagery is not as susceptible to environmental effects, however thermal imaging sensors are more sensitive to noise and they are only gray scale, making distinguishing between objects difficult. Several approaches to combining the visual and thermal modalities have been proposed, however they are limited by assuming that both modalities are perfuming equally well. When one modality fails, existing approaches are unable to detect the drop in performance and disregard the under performing modality. In this paper, a novel middle fusion approach for combining visual and thermal spectrum images for object tracking is proposed. Motion and object detection is performed on each modality and the object detection results for each modality are fused base on the current performance of each modality. Modality performance is determined by comparing the number of objects tracked by the system with the number detected by each mode, with a small allowance made for objects entering and exiting the scene. The tracking performance of the proposed fusion scheme is compared with performance of the visual and thermal modes individually, and a baseline middle fusion scheme. Improvement in tracking performance using the proposed fusion approach is demonstrated. The proposed approach is also shown to be able to detect the failure of an individual modality and disregard its results, ensuring performance is not degraded in such situations.

Testing of a distributed generation system with a virtual grid

The paper proposes a solution for testing of a physical distributed generation system (DGs) along with a computer simulated network. The computer simulated network is referred as the virtual grid in this paper. Integration of DG with the virtual grid provides broad area of testing of power supplying capability and dynamic performance of a DG. It is shown that a DG can supply a part of load power while keeping Point of Common Coupling (PCC) voltage magnitude constant. To represent the actual load, a universal load along with power regenerative capability is designed with the help of voltage source converter (VSC) that mimics the load characteristic. The overall performance of the proposed scheme is verified using computer simulation studies.

Improved power sharing among distributed generators using web based communication

This paper investigates the possibility of power sharing improvements amongst distributed generators with low cost, low bandwidth communications. Decentralized power sharing or power management can be improved significantly with low bandwidth communication. Utility intranet or a dedicated web based communication can serve the purpose. The effect of network parameter such line impedance, R/X ratio on decentralized power sharing can be compensated with correction in the decentralized control reference quantities through the low bandwidth communication. In this paper, the possible improvement is demonstrated in weak system condition, where the micro sources and the loads are not symmetrical along the rural microgrid with high R/X ratio line, creates challenge for decentralized control. In those cases the web based low bandwidth communication is economic and justified than costly advance high bandwidth communication.

A comparative study of the methods of inclusion of PMU current phasor measurements in a hybrid state estimator

The paper compares three different methods of inclusion of current phasor measurements by phasor measurement units (PMUs) in the conventional power system state estimator. For each of the three methods, comprehensive formulation of the hybrid state estimator in the presence of conventional and PMU measurements is presented. The performance of the state estimator in the presence of conventional measurements and optimally placed PMUs is evaluated in terms of convergence characteristics and estimator accuracy. Test results on the IEEE 14-bus and IEEE 300-bus systems are analyzed to determine the best possible method of inclusion of PMU current phasor measurements.

Robust image hashing using higher order spectral features

Robust image hashing seeks to transform a given input image into a shorter hashed version using a key-dependent non-invertible transform. These image hashes can be used for watermarking, image integrity authentication or image indexing for fast retrieval. This paper introduces a new method of generating image hashes based on extracting Higher Order Spectral features from the Radon projection of an input image. The feature extraction process is non-invertible, non-linear and different hashes can be produced from the same image through the use of random permutations of the input. We show that the transform is robust to typical image transformations such as JPEG compression, noise, scaling, rotation, smoothing and cropping. We evaluate our system using a verification-style framework based on calculating false match, false non-match likelihoods using the publicly available Uncompressed Colour Image database (UCID) of 1320 images. We also compare our results to Swaminathan’s Fourier-Mellin based hashing method with at least 1% EER improvement under noise, scaling and sharpening.

A new method for improving reliability and line loss in distribution networks

In this paper, both Distributed Generators (DG) and capacitors are allocated and sized optimally for improving line loss and reliability. The objective function is composed of the investment cost of DGs and capacitors along with loss and reliability which are converted to the genuine dollar. The bus voltage and line current are considered as constraints which should be satisfied during the optimization procedure. Hybrid Particle Swarm Optimization as a heuristic based technique is used as the optimization method. The IEEE 69-bus test system is modified and employed to evaluate the proposed algorithm. The results illustrate that the lowest cost planning is found by optimizing both DGs and capacitors in distribution networks.

Crowd counting using group tracking and local features

In public venues, crowd size is a key indicator of crowd safety and stability. In this paper we propose a crowd counting algorithm that uses tracking and local features to count the number of people in each group as represented by a foreground blob segment, so that the total crowd estimate is the sum of the group sizes. Tracking is employed to improve the robustness of the estimate, by analysing the history of each group, including splitting and merging events. A simplified ground truth annotation strategy results in an approach with minimal setup requirements that is highly accurate.