12 resultados para robotic palletising

em Aston University Research Archive


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In this paper a surgical robotic device for cochlear implantation surgery is described that is able to discriminate tissue interfaces and other controlling parameters ahead of a drill tip. The advantage in surgery is that tissues at interfaces can be preserved. The smart tool is able to control interaction with respect to the flexing tissue to avoid penetration control the extent of protrusion with respect to the real-time position of the tissue. To interpret drilling conditions, and conditions leading up to breakthrough at a tissue interface, the sensing scheme used enables discrimination between the variety of conditions posed in the drilling environment. The result is a robust fully autonomous system able to respond to tissue type, behaviour and deflection in real-time. The paper describes the robotic tool that has been designed to be used in the surgical environment where it has been used in the operating room.

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This thesis described the research carried out on the development of a novel hardwired tactile sensing system tailored for the application of a next generation of surgical robotic and clinical devices, namely a steerable endoscope with tactile feedback, and a surface plate for patient posture and balance. Two case studies are examined. The first is a one-dimensional sensor for the steerable endoscope retrieving shape and ‘touch’ information. The second is a two-dimensional surface which interprets the three-dimensional motion of a contacting moving load. This research can be used to retrieve information from a distributive tactile sensing surface of a different configuration, and can interpret dynamic and static disturbances. This novel approach to sensing has the potential to discriminate contact and palpation in minimal invasive surgery (MIS) tools, and posture and balance in patients. The hardwired technology uses an embedded system based on Field Programmable Gate Arrays (FPGA) as the platform to perform the sensory signal processing part in real time. High speed robust operation is an advantage from this system leading to versatile application involving dynamic real time interpretation as described in this research. In this research the sensory signal processing uses neural networks to derive information from input pattern from the contacting surface. Three neural network architectures namely single, multiple and cascaded were introduced in an attempt to find the optimum solution for discrimination of the contacting outputs. These architectures were modelled and implemented into the FPGA. With the recent introduction of modern digital design flows and synthesis tools that essentially take a high-level sensory processing behaviour specification for a design, fast prototyping of the neural network function can be achieved easily. This thesis outlines the challenge of the implementations and verifications of the performances.

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This thesis applies a hierarchical latent trait model system to a large quantity of data. The motivation for it was lack of viable approaches to analyse High Throughput Screening datasets which maybe include thousands of data points with high dimensions. High Throughput Screening (HTS) is an important tool in the pharmaceutical industry for discovering leads which can be optimised and further developed into candidate drugs. Since the development of new robotic technologies, the ability to test the activities of compounds has considerably increased in recent years. Traditional methods, looking at tables and graphical plots for analysing relationships between measured activities and the structure of compounds, have not been feasible when facing a large HTS dataset. Instead, data visualisation provides a method for analysing such large datasets, especially with high dimensions. So far, a few visualisation techniques for drug design have been developed, but most of them just cope with several properties of compounds at one time. We believe that a latent variable model (LTM) with a non-linear mapping from the latent space to the data space is a preferred choice for visualising a complex high-dimensional data set. As a type of latent variable model, the latent trait model can deal with either continuous data or discrete data, which makes it particularly useful in this domain. In addition, with the aid of differential geometry, we can imagine the distribution of data from magnification factor and curvature plots. Rather than obtaining the useful information just from a single plot, a hierarchical LTM arranges a set of LTMs and their corresponding plots in a tree structure. We model the whole data set with a LTM at the top level, which is broken down into clusters at deeper levels of t.he hierarchy. In this manner, the refined visualisation plots can be displayed in deeper levels and sub-clusters may be found. Hierarchy of LTMs is trained using expectation-maximisation (EM) algorithm to maximise its likelihood with respect to the data sample. Training proceeds interactively in a recursive fashion (top-down). The user subjectively identifies interesting regions on the visualisation plot that they would like to model in a greater detail. At each stage of hierarchical LTM construction, the EM algorithm alternates between the E- and M-step. Another problem that can occur when visualising a large data set is that there may be significant overlaps of data clusters. It is very difficult for the user to judge where centres of regions of interest should be put. We address this problem by employing the minimum message length technique, which can help the user to decide the optimal structure of the model. In this thesis we also demonstrate the applicability of the hierarchy of latent trait models in the field of document data mining.

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Students at Cranfield Manufacturing Systems Centre helped Brompton Bikes formulate a strategy to meet rapid sales growth. The students took up Operations Excellence MSc, a two-year part-time programme based on the Cranfield MSc in Engineering and Management of Manufacturing Systems, include the Realising Competitive Manufacture module, which is set out to consolidate and embed the knowledge and skills developed throughout the two-year programme. Guided by StratNav process, the students analysed the product families of Brompton, established the basis on which they compete in the market place, and then benchmarked against key competitors. The top five developments identified to be needed by Brompton are: the formation of group technology cells, creation of a robotic brazing facility, and training and recruitment initiatives for production staff.

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Flexible Assembly Systems (FASs) are normally associated with the automatic, or robotic, assembly of products, supported by automated material handling systems. However, manual assembly operations are still prevalent within many industries, where the complexity and variety of products prohibit the development of suitable automated assembly equipment. This article presents a generic model for incorporating flexibility into the design and control of assembly operations concerned with high variety/low volume manufacture, drawing on the principles for Flexible Manufacturing Systems (FMS) and Just-in-Time (JIT) delivery. It is based on work being undertaken in an electronics company where the assembly operations have been overhauled and restructured in response to a need for greater flexibility, shorter cycle times and reduced inventory levels. The principles employed are in themselves not original. However, the way they have been combined and tailored has created a total manufacturing control system which represents a new concept for responding to demands placed on market driven firms operating in an uncertain environment.

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Tactile sensors are needed for many emerging robotic and telepresence applications such as keyhole surgery and robot operation in unstructured environments. We have proposed and demonstrated a tactile sensor consisting of a fibre Bragg grating embedded in a polymer "finger". When the sensor is placed in contact with a surface and translated tangentially across it measurements on the changes in the reflectivity spectrum of the grating provide a measurement of the spatial distribution of forces perpendicular to the surface and thus, through the elasticity of the polymer material, to the surface roughness. Using a sensor fabricated from a Poly Siloxane polymer (Methyl Vinyl Silicone rubber) spherical cap 50 mm in diameter, 6 mm deep with an embedded 10 mm long Bragg grating we have characterised the first and second moment of the grating spectral response when scanned across triangular and semicircular periodic structures both with a modulation depth of 1 mm and a period of 2 mm. The results clearly distinguish the periodicity of the surface structure and the differences between the two different surface profiles. For the triangular structure a central wavelength modulation of 4 pm is observed and includes a fourth harmonic component, the spectral width is modulated by 25 pm. Although crude in comparison to human senses these results clearly shown the potential of such a sensor for tactile imaging and we expect that with further development in optimising both the grating and polymer "finger" properties a much increased sensitivity and spatial resolution is achievable.

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Padilha’s new Robocop film can be read in the light of Paul Virilio’s theoretical work, notably Desert Screen. Robocop serves as the city’s warrior but also as a munition in the hands of global media forces. Still, even if the film presents the fallibility of robotic technology, its true failure is in sustaining the progressivist myth of technology perfectly under human control.

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Background: Cochleostomy formation is a key stage of the cochlear implantation procedure. Minimizing the trauma sustained by the cochlea during this step is thought to be a critical feature in hearing preservation cochlear implantation. The aim of this paper is firstly, to assess the cochlea disturbances during manual and robotic cochleostomy formation. Secondly, to determine whether the use of a smart micro-drill is feasible during human cochlear implantation. Materials and methods: The disturbances within the cochlea during cochleostomy formation were analysed in a porcine specimen by creating a third window cochleostomy, preserving the underlying endosteal membrane, on the anterior aspect of the basal turn of the cochlea. A laser vibrometer was aimed at this third window, to assess its movement while a traditional cochleostomy was performed. Six cochleostomies were performed in total, three manually and three with a smart micro-drill. The mean and peak membrane movement was calculated for both manual and smart micro-drill arms, to represent the disturbances sustained within cochlea during cochleostomy formation. The smart micro-drill was further used to perform live human robotic cochleostomies on three adult patients who met the National Institute of Health and Clinical Excellence criteria for undergoing cochlear implantation. Results: In the porcine trial, the smart micro-drill preserved the endosteal membrane in all three cases. The velocity of movement of the endosteal membrane during manual cochleostomy is approximately 20 times higher on average and 100 times greater in peak velocity, than for robotic cochleostomy. The robot was safely utilized in theatre in all three cases and successfully created a bony cochleostomy while preserving the underlying endosteal membrane. Conclusions: Our experiments have revealed that controlling the force of drilling during cochleostomy formation and opening the endosteal membrane with a pick will minimize the trauma sustained by the cochlea by a factor of 20. Additionally, the smart micro-drill can safely perform a bony cochleostomy in humans under operative conditions and preserve the integrity of the underlying endosteal membrane. © W. S. Maney & Son Ltd 2013.

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In the Light Controlled Factory part-to-part assembly and reduced weight will be enabled through the use of predictive fitting processes; low cost high accuracy reconfigurable tooling will be made possible by active compensation; improved control will allow accurate robotic machining; and quality will be improved through the use of traceable uncertainty based quality control throughout the production system. A number of challenges must be overcome before this vision will be realized; 1) controlling industrial robots for accurate machining; 2) compensation of measurements for thermal expansion; 3) Compensation of measurements for refractive index changes; 4) development of Embedded Metrology Tooling for in-tooling measurement and active tooling compensation; and 5) development of Software for the Planning and Control of Integrated Metrology Networks based on Quality Control with Uncertainty Evaluation and control systems for predictive processes. This paper describes how these challenges are being addressed, in particular the central challenge of developing large volume measurement process models within an integrated dimensional variation management (IDVM) system.

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The concept of measurement-enabled production is based on integrating metrology systems into production processes and generated significant interest in industry, due to its potential to increase process capability and accuracy, which in turn reduces production times and eliminates defective parts. One of the most promising methods of integrating metrology into production is the usage of external metrology systems to compensate machine tool errors in real time. The development and experimental performance evaluation of a low-cost, prototype three-axis machine tool that is laser tracker assisted are described in this paper. Real-time corrections of the machine tool's absolute volumetric error have been achieved. As a result, significant increases in static repeatability and accuracy have been demonstrated, allowing the low-cost three-axis machine tool to reliably reach static positioning accuracies below 35 μm throughout its working volume without any prior calibration or error mapping. This is a significant technical development that demonstrated the feasibility of the proposed methods and can have wide-scale industrial applications by enabling low-cost and structural integrity machine tools that could be deployed flexibly as end-effectors of robotic automation, to achieve positional accuracies that were the preserve of large, high-precision machine tools.

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This article describes a surgical robotic device that is able to discriminate tissue interfaces and other controlling parameters ahead of the drill tip. The advantage in such a surgery is that the tissues at the interfaces can be preserved. A smart tool detects ahead of the tool point and is able to control the interaction with respect to the flexing tissue, to avoid penetration or to control the extent of protrusion with respect to the position of the tissue. For surgical procedures, where precision is required, the tool offers significant benefit. To interpret the drilling conditions and the conditions leading up to breakthrough at a tissue interface, a sensing scheme is used that discriminates between the variety of conditions posed in the drilling environment. The result is a fully autonomous system, which is able to respond to the tissue type, behaviour, and deflection in real-time. The system is also robust in terms of disturbances encountered in the operating theatre. The device is pragmatic. It is intuitive to use, efficient to set up, and uses standard drill bits. The micro-drill, which has been used to prepare cochleostomies in the theatre, was used to remove the bone tissue leaving the endosteal membrane intact. This has enabled the preservation of sterility and the drilling debris to be removed prior to the insertion of the electrode. It is expected that this technique will promote the preservation of hearing and reduce the possibility of complications. The article describes the device (including simulated drill progress and hardware set-up) and the stages leading up to its use in the theatre. © 2010 Authors.