647 resultados para Appearance-based Navigation
Resumo:
This paper considers the question of designing a fully image based visual servo control for a dynamic system. The work is motivated by the ongoing development of image based visual servo control of small aerial robotic vehicles. The observed targets considered are coloured blobs on a flat surface to which the normal direction is known. The theoretical framework is directly applicable to the case of markings on a horizontal floor or landing field. The image features used are a first order spherical moment for position and an image flow measurement for velocity. A fully non-linear adaptive control design is provided that ensures global stability of the closed-loop system. © 2005 IEEE.
Resumo:
Describes how many of the navigation techniques developed by the robotics research community over the last decade may be applied to a class of underground mining vehicles (LHDs and haul trucks). We review the current state-of-the-art in this area and conclude that there are essentially two basic methods of navigation applicable. We describe an implementation of a reactive navigation system on a 30 tonne LHD which has achieved full-speed operation at a production mine.
Resumo:
US state-based data breach notification laws have unveiled serious corporate and government failures regarding the security of personal information. These laws require organisations to notify persons who may be affected by an unauthorized acquisition of their personal information. Safe harbours to notification exist if personal information is encrypted. Three types of safe harbour have been identified in the literature: exemptions, rebuttable presumptions and factors. The underlying assumption of exemptions is that encrypted personal information is secure and therefore unauthorized access does not pose a risk. However, the viability of this assumption is questionable when examined against data breaches involving encrypted information and the demanding practical requirements of effective encryption management. Recent recommendations by the Australian Law Reform Commission (ALRC) would amend the Privacy Act 1988 (Cth) to implement a data breach scheme that includes a different type of safe harbour, factor based analysis. The authors examine the potential capability of the ALRC’s proposed encryption safe harbour in relation to the US experience at the state legislature level.
Resumo:
Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of the sensors involved (as opposed to radar). This paper describes the development and evaluation of a vision-based collision detection algorithm suitable for fixed-wing aerial robotics. The system was evaluated using highly realistic vision data of the moments leading up to a collision. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We make use of the enormous potential of graphic processing units to achieve processing rates of 30Hz (for images of size 1024-by- 768). Currently, integration in the final platform is under way.
Resumo:
Evidence-based practice is increasingly being recognised as an important issue in a range of professional contexts including education, nursing, occupational therapy and librarianship. Many of these professions have observed a relationship or interface between evidence-based practice and information literacy. Using a phenomenographic approach this research explores variation in the how library and information professionals are experiencing evidence-based practice as part of their professional work. The findings of the research provide a basis for arguing that evidence-based practice represents the professional's enactment of information literacy in the workplace.
Resumo:
Machine vision represents a particularly attractive solution for sensing and detecting potential collision-course targets due to the relatively low cost, size, weight, and power requirements of vision sensors (as opposed to radar and TCAS). This paper describes the development and evaluation of a real-time vision-based collision detection system suitable for fixed-wing aerial robotics. Using two fixed-wing UAVs to recreate various collision-course scenarios, we were able to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. This type of image data is extremely scarce and was invaluable in evaluating the detection performance of two candidate target detection approaches. Based on the collected data, our detection approaches were able to detect targets at distances ranging from 400m to about 900m. These distances (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning of between 8-10 seconds ahead of impact, which approaches the 12.5 second response time recommended for human pilots. We overcame the challenge of achieving real-time computational speeds by exploiting the parallel processing architectures of graphics processing units found on commercially-off-the-shelf graphics devices. Our chosen GPU device suitable for integration onto UAV platforms can be expected to handle real-time processing of 1024 by 768 pixel image frames at a rate of approximately 30Hz. Flight trials using manned Cessna aircraft where all processing is performed onboard will be conducted in the near future, followed by further experiments with fully autonomous UAV platforms.
Resumo:
This paper describes a biologically inspired approach to vision-only simultaneous localization and mapping (SLAM) on ground-based platforms. The core SLAM system, dubbed RatSLAM, is based on computational models of the rodent hippocampus, and is coupled with a lightweight vision system that provides odometry and appearance information. RatSLAM builds a map in an online manner, driving loop closure and relocalization through sequences of familiar visual scenes. Visual ambiguity is managed by maintaining multiple competing vehicle pose estimates, while cumulative errors in odometry are corrected after loop closure by a map correction algorithm. We demonstrate the mapping performance of the system on a 66 km car journey through a complex suburban road network. Using only a web camera operating at 10 Hz, RatSLAM generates a coherent map of the entire environment at real-time speed, correctly closing more than 51 loops of up to 5 km in length.
Resumo:
RatSLAM is a vision-based SLAM system based on extended models of the rodent hippocampus. RatSLAM creates environment representations that can be processed by the experience mapping algorithm to produce maps suitable for goal recall. The experience mapping algorithm also allows RatSLAM to map environments many times larger than could be achieved with a one to one correspondence between the map and environment, by reusing the RatSLAM maps to represent multiple sections of the environment. This paper describes experiments investigating the effects of the environment-representation size ratio and visual ambiguity on mapping and goal navigation performance. The experiments demonstrate that system performance is weakly dependent on either parameter in isolation, but strongly dependent on their joint values.
Resumo:
The Simultaneous Localisation And Mapping (SLAM) problem is one of the major challenges in mobile robotics. Probabilistic techniques using high-end range finding devices are well established in the field, but recent work has investigated vision-only approaches. We present an alternative approach to the leading existing techniques, which extracts approximate rotational and translation velocity information from a vehicle-mounted consumer camera, without tracking landmarks. When coupled with an existing SLAM system, the vision module is able to map a 45 metre long indoor loop and a 1.6 km long outdoor road loop, without any parameter or system adjustment between tests. The work serves as a promising pilot study into ground-based vision-only SLAM, with minimal geometric interpretation of the environment.
Resumo:
Practice based research appears to have emerged within several Higher Education agendas including the professional doctorates and the teacher as researcher. One way of thinking about this methodological approach is to consider its research paradigm – a practice based epistemology, and from this perspective to consider what special application to research supervision the paradigm invites. Within a “supervision as pedagogy” agenda these applications can be considered as pedagogies. This paper has been written in the style of practice based research, drawing on the author’s own experiences of supervising students undertaking practice based research. It adopts a position that research supervision is pedagogy and draws on the model of ‘Productive Pedagogies” to articulate strategies to help novice research students develop a research proposal.
Resumo:
The RatSLAM system can perform vision based SLAM using a computational model of the rodent hippocampus. When the number of pose cells used to represent space in RatSLAM is reduced, artifacts are introduced that hinder its use for goal directed navigation. This paper describes a new component for the RatSLAM system called an experience map, which provides a coherent representation for goal directed navigation. Results are presented for two sets of real world experiments, including comparison with the original goal memory system's performance in the same environment. Preliminary results are also presented demonstrating the ability of the experience map to adapt to simple short term changes in the environment.
Resumo:
Background Colorectal cancer survivors may suffer from a range of ongoing psychosocial and physical problems that negatively impact on quality of life. This paper presents the study protocol for a novel telephone-delivered intervention to improve lifestyle factors and health outcomes for colorectal cancer survivors. Methods/Design Approximately 350 recently diagnosed colorectal cancer survivors will be recruited through the Queensland Cancer Registry and randomised to the intervention or control condition. The intervention focuses on symptom management, lifestyle and psychosocial support to assist participants to make improvements in lifestyle factors (physical activity, healthy diet, weight management, and smoking cessation) and health outcomes. Participants will receive up to 11 telephone-delivered sessions over a 6 month period from a qualified health professional or 'health coach'. Data collection will occur at baseline (Time 1), post-intervention or six months follow-up (Time 2), and at 12 months follow-up for longer term effects (Time 3). Primary outcome measures will include physical activity, cancer-related fatigue and quality of life. A cost-effective analysis of the costs and outcomes for survivors in the intervention and control conditions will be conducted from the perspective of health care costs to the government. Discussion The study will provide valuable information about an innovative intervention to improve lifestyle factors and health outcomes for colorectal cancer survivors.
Resumo:
PURPOSE: We report our telephone-based system for selecting community control series appropriate for a complete Australia-wide series of Ewing's sarcoma cases. METHODS: We used electronic directory random sampling to select age-matched controls. The sampling has all listed telephone numbers on an up-dated CD-Rom. RESULTS: 95% of 2245 telephone numbers selected were successfully contacted. The mean number of attempts needed was 1.94, 58% answering at the first attempt. On average, we needed 4.5 contacts per control selected. Calls were more likely to be successful (reach a respondent) when made in the evening (except Saturdays). The overall response rate among contacted telephone numbers was 92.8%. Participation rates among female and male respondents were practically the same. The exclusion of unlisted numbers (13.5% of connected households) and unconnected households (3.7%) led to potential selection bias. However, restricting the case series to listed cases only, plus having external information on the direction of potential bias allow meaningful interpretation of our data. CONCLUSION: Sampling from an electronic directory is convenient, economical and simple, and gives a very good yield of eligible subjects compared to other methods.
Resumo:
Introduction This chapter traces the history of evidence-based practice from its roots in evidence-based medicine to contemporary thinking about the usefulness of such an approach to practice. It defines evidence-based practice and differentiates it from terms such as evidence-based medicine, evidence-based policy and evidence-based healthcare. As evidence-based practice is concerned with identifying ‘good evidence’, this chapter will first describe the nature and production of knowledge, as it is important to understand the subjective nature of knowledge and the research process. The chapter considers the necessary skills for evidence-based practice, and discusses the processes of attaining the necessary evidence and its limitations. We examine the barriers and facilitators to identifying and implementing ‘best practice’ and when evidence-based practice is appropriate to use. The chapter concludes with a discussion about the limitations of evidence-based practice and the potential use of other sources of information to guide practice.
Resumo:
Approaches with Vertical Guidance (APV) can provide greater safety and cost savings to general aviation through accurate GPS horizontal and vertical navigation. However, GPS needs augmentation to achieve APV fault detection requirements. Aircraft Based Augmentation Systems (ABAS) fuse GPS with additional sensors at the aircraft. Typical ABAS designs assume high-quality inertial sensors with Kalman filters but these are too expensive for general aviation. Instead of using high-quality (and expensive) sensors, the purpose of this paper is to investigate augmenting GPS with a low-quality MEMS IMU and Aircraft Dynamic Model (ADM). The IMU and ADM are fused together using a multiple model fusion strategy in a bank of Extended Kalman Filters (EKF) with the Normalized Solution Separation (NSS) fault detection scheme. A tightly-coupled configuration with GPS is used and frequent GPS updates are applied to the IMU and ADM to compensate for their errors. Based upon a simulated APV approach, the performance of this architecture in detecting a GPS ramp fault is investigated showing a performance improvement over a GPS-only “snapshot” implementation of the NSS method. The effect of fusing the IMU with the ADM is evaluated by comparing a GPS-IMU-ADM EKF with a GPS-IMU EKF where a small improvement in protection levels is shown.