889 resultados para technology and Automation
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The mining industry is highly suitable for the application of robotics and automation technology since the work is both arduous and dangerous. Visual servoing is a means of integrating noncontact visual sensing with machine control to augment or replace operator based control. This article describes two of our current mining automation projects in order to demonstrate some, perhaps unusual, applications of visual servoing, and also to illustrate some very real problems with robust computer vision
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The Field and Service Robotics (FSR) conference is a single track conference with a specific focus on field and service applications of robotics technology. The goal of FSR is to report and encourage the development of field and service robotics. These are non-factory robots, typically mobile, that must operate in complex and dynamic environments. Typical field robotics applications include mining, agriculture, building and construction, forestry, cargo handling and so on. Field robots may operate on the ground (of Earth or planets), under the ground, underwater, in the air or in space. Service robots are those that work closely with humans, importantly the elderly and sick, to help them with their lives. The first FSR conference was held in Canberra, Australia, in 1997. Since then the meeting has been held every 2 years in Asia, America, Europe and Australia. It has been held in Canberra, Australia (1997), Pittsburgh, USA (1999), Helsinki, Finland (2001), Mount Fuji, Japan (2003), Port Douglas, Australia (2005), Chamonix, France (2007), Cambridge, USA (2009), Sendai, Japan (2012) and most recently in Brisbane, Australia (2013). This year we had 54 submissions of which 36 were selected for oral presentation. The organisers would like to thank the international committee for their invaluable contribution in the review process ensuring the overall quality of contributions. The organising committee would also like to thank Ben Upcroft, Felipe Gonzalez and Aaron McFadyen for helping with the organisation and proceedings. and proceedings. The conference was sponsored by the Australian Robotics and Automation Association (ARAA), CSIRO, Queensland University of Technology (QUT), Defence Science and Technology Organisation Australia (DSTO) and the Rio Tinto Centre for Mine Automation, University of Sydney.
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Draglines are used extensively for overburden stripping in Australian open cut coal mines. This paper outlines the design of a computer control system to implement an automated swing cycle on a production dragline. Subsystems and sensors have been developed to satisfy the constraints imposed by the task, the harsh operating environment and the mines production requirements.
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This paper discusses some of the sensing technologies and control approaches available for guiding robot manipulators for a class of underground mining tasks including drilling jumbos, bolting arms, shotcreters or explosive chargers. Data acquired with such sensors, in the laboratory and underground, is presented.
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This paper presents a novel vision-based underwater robotic system for the identification and control of Crown-Of-Thorns starfish (COTS) in coral reef environments. COTS have been identified as one of the most significant threats to Australia's Great Barrier Reef. These starfish literally eat coral, impacting large areas of reef and the marine ecosystem that depends on it. Evidence has suggested that land-based nutrient runoff has accelerated recent outbreaks of COTS requiring extensive use of divers to manually inject biological agents into the starfish in an attempt to control population numbers. Facilitating this control program using robotics is the goal of our research. In this paper we introduce a vision-based COTS detection and tracking system based on a Random Forest Classifier (RFC) trained on images from underwater footage. To track COTS with a moving camera, we embed the RFC in a particle filter detector and tracker where the predicted class probability of the RFC is used as an observation probability to weight the particles, and we use a sparse optical flow estimation for the prediction step of the filter. The system is experimentally evaluated in a realistic laboratory setup using a robotic arm that moves a camera at different speeds and heights over a range of real-size images of COTS in a reef environment.
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In this report an artificial neural network (ANN) based automated emergency landing site selection system for unmanned aerial vehicle (UAV) and general aviation (GA) is described. The system aims increase safety of UAV operation by emulating pilot decision making in emergency landing scenarios using an ANN to select a safe landing site from available candidates. The strength of an ANN to model complex input relationships makes it a perfect system to handle the multicriteria decision making (MCDM) process of emergency landing site selection. The ANN operates by identifying the more favorable of two landing sites when provided with an input vector derived from both landing site's parameters, the aircraft's current state and wind measurements. The system consists of a feed forward ANN, a pre-processor class which produces ANN input vectors and a class in charge of creating a ranking of landing site candidates using the ANN. The system was successfully implemented in C++ using the FANN C++ library and ROS. Results obtained from ANN training and simulations using randomly generated landing sites by a site detection simulator data verify the feasibility of an ANN based automated emergency landing site selection system.
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Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.
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The integration of technology in care is core business in nursing and this role requires that we must understand and use technology informed by evidence that goes much deeper and broader than actions and behaviours. We need to delve more deeply into its complexity because there is nothing minor or insignificant about technology as a major influence in healthcare outcomes and experiences. Evidence is needed that addresses technology and nursing from perspectives that examine the effects of technology, especially related to increasing demands for efficiency, the relationship of technology to nursing and caring, and a range of philosophical questions associated with empowering people in their healthcare choices. Specifically, there is a need to confront in practice the ways technique influences care. Technique is the creation of a kind of thinking that is necessary for contemporary healthcare technology to develop and be applied in an efficient and rational manner. Technique is not an entity or specific thing, but rather a way of thinking that seeks to shape and organize nursing activity, and manage efficiently individual difference(s) in care. It emphasizes predetermined causal relationships, conformity, and sameness of product, process, and thought. In response is needed a radical vision of nursing that attempts in a real sense to ensure we meet the needs of individuals and their community. Activism and advocacy are needed, and a willingness to create a certain detachment from the imperatives that technique demands. It is argued that our responsibility as nurses is to respond in practice to the errors, advantages, difficulties, and temptations of technology for the benefit of those who most need our assistance and care.
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To enhance the sustainability of marine finfish aquaculture in the Asia-Pacific (AP) region by improving hatchery production technology and facilitating the uptake of compounded feeds for grow-out.
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Past issues of Fibreculture have examined activist philosophies from angles such as social justice and networked organisational forms, communication rights and net neutrality debates, and the push back against precarious new media labour. Our issue extends this work by capturing the complexities associated with the use of technology in activist contexts, and offering insights into how practitioners, scholars, and the makers of digital and networked technologies do and might need to work more collaboratively and pragmatically to address social justice issues.
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We discuss three approaches to the use of technology as a teaching and learning tool that we are currently implementing for a target group of about one hundred second level engineering mathematics students. Central to these approaches is the underlying theme of motivating relatively poorly motivated students to learn, with the aim of improving learning outcomes. The approaches to be discussed have been used to replace, in part, more traditional mathematics tutorial sessions and lecture presentations. In brief, the first approach involves the application of constructivist thinking in the tertiary education arena, using technology as a computational and visual tool to create motivational knowledge conflicts or crises. The central idea is to model a realistic process of how scientific theory is actually developed, as proposed by Kuhn (1962), in contrast to more standard lecture and tutorial presentations. The second approach involves replacing procedural or algorithmic pencil-and-paper skills-consolidation exercises by software based tasks. Finally, the third approach aims at creating opportunities for higher order thinking via "on-line" exploratory or discovery mode tasks. The latter incorporates the incubation period method, as originally discussed by Rubinstein (1975) and others.
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Background Diabetic foot ulcers (DFU) are a leading cause of diabetes-related hospitalisation and can be costly to manage without access to appropriate expert care. Within Queensland and indeed across many parts of Australia, there is an inequality in accessing specialist services for individuals with DFU. Recent National Health and Medical Research Council (NHMRC) diabetic foot guidelines recommend remote expert consultation with digital imaging should be made available to people with DFU to improve their clinical outcomes. Telemedicine appears to show promise in improving access to diabetic foot specialist services; however diabetic foot telemedicine models to date have relied upon videoconferencing, store and forward technology and/or customised appliances to obtain digital imagery which all require either expensive infrastructure or a timed reply to the request for advice. Whilst mobile phone advice services have been used with success in general diabetes management and telehealth services have improved diabetic foot outcomes, the rapid emergence in the use of mobile phones has established a need to review the role that various forms of telemedicine play in the management of DFU. The aim of this paper is to review traditional telemedicine modalities that have been used in the management of DFU and to compare that to new and innovative technology that are emerging. Process Studies investigating the management of DFU using various forms of telemedicine interventions will be included in this review. They include the use of videoconferencing technology, hand held digital still photography purpose built imaging devices and mobile phone imagery. Electronic databases (Pubmed, Medline and CINAHL) will be searched using broad MeSH terms and keywords that cover the intended area of interest. Findings It is anticipated that the results of this narrative review will provide delegates of the 2015 Australasian Podiatry Conference an insight into the types of emerging innovative diagnostic telemedicine technologies in the management of DFU against the backdrop of traditional and evidence based modalities. It is anticipated that the findings will drive further research in the area of mobile phone imagery and innovation in the management of DFU.
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A randomised and population-based screening design with new technologies has been applied to the organised cervical cancer screening programme in Finland. In this experiment the women invited to routine five-yearly screening are individually randomised to be screened with automation-assisted cytology, human papillomavirus (HPV) test or conventional cytology. By using the randomised design, the ultimate aim is to assess and compare the long-term outcomes of the different screening regimens. The primary aim of the current study was to evaluate, based on the material collected during the implementation phase of the Finnish randomised screening experiment, the cross-sectional performance and validity of automation-assisted cytology (Papnet system) and primary HPV DNA testing (Hybrid Capture II assay for 13 oncogenic HPV types) within service screening, in comparison to conventional cytology. The parameters of interest were test positivity rate, histological detection rate, relative sensitivity, relative specificity and positive predictive value. Also, the effect of variation in performance by screening laboratory on age-adjusted cervical cancer incidence was assessed. Based on the cross-sectional results, almost no differences were observed in the performance of conventional and automation-assisted screening. Instead, primary HPV screening found 58% (95% confidence interval 19-109%) more cervical lesions than conventional screening. However, this was mainly due to overrepresentation of mild- and moderate-grade lesions and, thus, is likely to result in overtreatment since a great deal of these lesions would never progress to invasive cancer. Primary screening with an HPV DNA test alone caused substantial loss in specificity in comparison to cytological screening. With the use of cytology triage test, the specificity of HPV screening improved close to the level of conventional cytology. The specificity of primary HPV screening was also increased by increasing the test positivity cutoff from the level recommended for clinical use, but the increase was more modest than the one gained with the use of cytology triage. The performance of the cervical cancer screening programme varied widely between the screening laboratories, but the variation in overall programme effectiveness between respective populations was more marginal from the very beginning of the organised screening activity. Thus, conclusive interpretations on the quality or success of screening should not be based on performance parameters only. In the evaluation of cervical cancer screening the outcome should be selected as closely as possible to the true measure of programme effectiveness, which is the number of invasive cervical cancers and subsequent deaths prevented in the target population. The evaluation of benefits and adverse effects of each new suggested screening technology should be performed before the technology becomes an accepted routine in the existing screening programme. At best, the evaluation is performed randomised, within the population and screening programme in question, which makes the results directly applicable to routine use.
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In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.
INTACTE: An Interconnect Area, Delay, and Energy Estimation Tool for Microarchitectural Explorations
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Prior work on modeling interconnects has focused on optimizing the wire and repeater design for trading off energy and delay, and is largely based on low level circuit parameters. Hence these models are hard to use directly to make high level microarchitectural trade-offs in the initial exploration phase of a design. In this paper, we propose INTACTE, a tool that can be used by architects toget reasonably accurate interconnect area, delay, and power estimates based on a few architecture level parameters for the interconnect such as length, width (in number of bits), frequency, and latency for a specified technology and voltage. The tool uses well known models of interconnect delay and energy taking into account the wire pitch, repeater size, and spacing for a range of voltages and technologies.It then solves an optimization problem of finding the lowest energy interconnect design in terms of the low level circuit parameters, which meets the architectural constraintsgiven as inputs. In addition, the tool also provides the area, energy, and delay for a range of supply voltages and degrees of pipelining, which can be used for micro-architectural exploration of a chip. The delay and energy models used by the tool have been validated against low level circuit simulations. We discuss several potential applications of the tool and present an example of optimizing interconnect design in the context of clustered VLIW architectures. Copyright 2007 ACM.