Practical constraints on real time Bayesian filtering for NDE applications

An experimental evaluation of Bayesian positional filtering algorithms applied to mobile robots for Non-Destructive Evaluation is presented using multiple positional sensing data – a real time, on-robot implementation of an Extended Kalman and Particle filter was used to control a robot performing representative raster scanning of a sample. Both absolute and relative positioning were employed – the absolute being an indoor acoustic GPS system that required careful calibration. The performance of the tracking algorithms are compared in terms of computational cost and the accuracy of trajectory estimates. It is demonstrated that for real time NDE scanning, the Extended Kalman Filter is a more sensible choice given the high computational overhead for the Particle filter

Determining position and orientation of a 3-wheel robot on a pipe using an accelerometer

Accurate positioning of robots on pipes is a challenge in automated industrial inspection. It is typically achieved using expensive and cumbersome external measurement equipment. This paper presents an Inverse Model method for determining the orientation angle (α ) and circumferential position angle (ω) of a 3 point of contact robot on a pipe where measurements are taken from a 3-axis accelerometer sensor. The advantage of this system is that it provides absolute positional measurements using only a robot mounted sensor. Two methods are presented which follow an analytical approximation to correct the estimated values. First, a correction factor found though a parametric study between the robot geometry and a given pipe radius, followed by an optimization solution which calculates the desired angles based on the system configuration, robot geometry and the output of a 3-axis accelerometer. The method is experimentally validated using photogrammetry measurements from a Vicon T160 positioning system to record the position of a three point of contact test rig in relation to a test pipe in a global reference frame. An accelerometer is attached to the 3 point of contact test rig which is placed at different orientation (α ) and circumferential position (ω) angles. This work uses a new method of processing data from an accelerometer sensor to obtain the α and ω angles. The experimental results show a maximum error of 3.40° in α and 4.17° in ω , where the ω circumferential positional error corresponds to ±18mm for the test pipe radius of 253mm

Remote inspection of wind turbine blades using UAV with photogrammetry payload

Visual Inspection is regularly used as a method of non-destructive testing (NDT) to find defects in large component structures. Wind turbine blades, regularly located in isolated environments, are typically difficult to access. In order to reduce operational and maintenance costs and extend asset lifetime, a project for the remote inspection of blades to accurately assess surface integrity is being undertaken. The remote inspection solution combines an unmanned aerial vehicle (UAV) with a photogrammetry payload to provide visual reconstruction of a blade for a holistic condition overview. Photogrammetric software is used to process the captured images to generate a 3D blade profile. A waypoint guidance algorithm controls the UAV to complete a full blade surface capture at constant distance, minimising motion blur. The results provide an accurate 3D reconstruction of the used blade complete with defects, discontinuities and markings and hence visual inspection using UAV combined with photogrammetry has been successfully implemented

Tactile imaging : the requirements to transition from screening to diagnosis of breast cancer - a concise review of current capabilities and strategic direction

This paper presents a review of Tactile Imaging, a developing technology for breast cancer screening finding traction in the marketplace. The paper identifies the necessary steps required to develop the technology from a screening method to the point where stand-alone diagnosis of suspected breast lesions can be performed without the need for a secondary care referral for a mammogram or biopsy. The relevant literature on Tactile Imaging is reviewed and current capabilities in academia are compared with those implemented in industry before being cross referenced with the metrics for breast cancer diagnosis. Tactile Imaging in academia has been shown to be capable of binary lesion classification and has seen extensive development, to where benign biopsy rates could be reduced by 23%. This has not been mirrored in the marketplace however, where market inertia relegates such systems to early warning screening only as an adjunct to mammography. Additionally, for detailed subclass diagnosis of breast conditions, more metrics are required than is currently available from Tactile Imaging at present. A detailed scheme of work is provided to achieve this. The additional metrics required for stand-alone diagnostics using Tactile Imaging are: background breast elasticity, lesion position on the breast, and lesion depth. These can estimate the lesion constituents and thus the histological diagnosis

Applications of tactile imaging in calibration-less and cuff-less blood pressure monitoring for home care

This paper presents a concise review of current Tactile Imaging research, and industrial innovations, applied to blood pressure (BP) measurements in home and ambulatory care. This paper also presents a review of current accepted methods in measuring blood pressure, with appropriate standards required for new and innovative measurement technologies. The application of Tactile Imaging in BP monitoring has led to several advances in industry and in literature, culminating in solutions implemented on widely available smartphones. Naturally such solutions have great appeal in home care markets, especially amongst the ‘worried well’ and fitness communities. However such systems do not see widespread uptake in clinical practice, with clinicians favoring more traditional measurement technologies despite continuous pressure from the public and clinicians for more accurate and comfortable systems. Though the reasoning for this is largely down to the strict standards for medical devices, and not a small amount of clinical inertia, it must be acknowledged that the mechanics and theory of operation of many incumbent noninvasive BP measurement systems are not well understood. This paper highlights the important findings and recent developments in calibration-less and cuff-less BP monitoring, based on Tactile Imaging, to aid others in advancing this rapidly developing field

Spatial calibration of large volume photogrammetry based metrology systems

Photogrammetry systems are used extensively as volumetric measurement tools in a diverse range of applications including gait analysis, robotics and computer generated animation. For precision applications the spatial inaccuracies of these systems are of interest. In this paper, an experimental characterisation of a six camera Vicon T160 photogrammetry system using a high accuracy laser tracker is presented. The study was motivated by empirical observations of the accuracy of the photogrammetry system varying as a function of location within a measurement volume of approximately 100 m3. Error quantification was implemented through simultaneously tracking a target scanned through a sub-volume (27 m3) using both systems. The position of the target was measured at each point of a grid in four planes at different heights. In addition, the effect of the use of passive and active calibration artefacts upon system accuracy was investigated. A convex surface was obtained when considering error as a function of position for a fixed height setting confirming the empirical observations when using either calibration artefact. Average errors of 1.48 mm and 3.95 mm were obtained for the active and passive calibration artefacts respectively. However, it was found that through estimating and applying an unknown scale factor relating measurements, the overall accuracy could be improved with average errors reducing to 0.51 mm and 0.59 mm for the active and passive datasets respectively. The precision in the measurements was found to be less than 10 μm for each axis