946 resultados para visual method
Resumo:
This paper presents a vision-based method of vehicle localisation that has been developed and tested on a large forklift type robotic vehicle which operates in a mainly outdoor industrial setting. The localiser uses a sparse 3D edgemap of the environment and a particle filter to estimate the pose of the vehicle. The vehicle operates in dynamic and non-uniform outdoor lighting conditions, an issue that is addressed by using knowledge of the scene to intelligently adjust the camera exposure and hence improve the quality of the information in the image. Results from the industrial vehicle are shown and compared to another laser-based localiser which acts as a ground truth. An improved likelihood metric, using peredge calculation, is presented and has shown to be 40% more accurate in estimating rotation. Visual localization results from the vehicle driving an arbitrary 1.5km path during a bright sunny period show an average position error of 0.44m and rotation error of 0.62deg.
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This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests.
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This paper demonstrates some interesting connections between the hitherto disparate fields of mobile robot navigation and image-based visual servoing. A planar formulation of the well-known image-based visual servoing method leads to a bearing-only navigation system that requires no explicit localization and directly yields desired velocity. The well known benefits of image-based visual servoing such as robustness apply also to the planar case. Simulation results are presented.
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In this paper, we outline the sensing system used for the visual pose control of our experimental car-like vehicle, the Autonomous Tractor. The sensing system consists of a magnetic compass, an omnidirectional camera and a low-resolution odometry system. In this work, information from these sensors is fused using complementary filters. Complementary filters provide a means of fusing information from sensors with different characteristics in order to produce a more reliable estimate of the desired variable. Here, the range and bearing of landmarks observed by the vision system are fused with odometry information and a vehicle model, providing a more reliable estimate of these states. We also present a method of combining a compass sensor with odometry and a vehicle model to improve the heading estimate.
Resumo:
Visual servoing has been a viable method of robot manipulator control for more than a decade. Initial developments involved positionbased visual servoing (PBVS), in which the control signal exists in Cartesian space. The younger method, image-based visual servoing (IBVS), has seen considerable development in recent years. PBVS and IBVS offer tradeoffs in performance, and neither can solve all tasks that may confront a robot. In response to these issues, several methods have been devised that partition the control scheme, allowing some motions to be performed in the manner of a PBVS system, while the remaining motions are performed using an IBVS approach. To date, there has been little research that explores the relative strengths and weaknesses of these methods. In this paper we present such an evaluation. We have chosen three recent visual servo approaches for evaluation in addition to the traditional PBVS and IBVS approaches. We posit a set of performance metrics that measure quantitatively the performance of a visual servo controller for a specific task. We then evaluate each of the candidate visual servo methods for four canonical tasks with simulations and with experiments in a robotic work cell.
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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.
Resumo:
This paper demonstrates some interesting connections between the hitherto disparate fields of mobile robot navigation and image-based visual servoing. A planar formulation of the well-known image-based visual servoing method leads to a bearing-only navigation system that requires no explicit localization and directly yields desired velocity. The well known benefits of image-based visual servoing such as robustness apply also to the planar case. Simulation results are presented.
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Localisation of an AUV is challenging and a range of inspection applications require relatively accurate positioning information with respect to submerged structures. We have developed a vision based localisation method that uses a 3D model of the structure to be inspected. The system comprises a monocular vision system, a spotlight and a low-cost IMU. Previous methods that attempt to solve the problem in a similar way try and factor out the effects of lighting. Effects, such as shading on curved surfaces or specular reflections, are heavily dependent on the light direction and are difficult to deal with when using existing techniques. The novelty of our method is that we explicitly model the light source. Results are shown of an implementation on a small AUV in clear water at night.
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We present a novel method for integrating GPS position estimates with position and attitude estimates derived from visual odometry using a scheme similar to a classic loosely-coupled GPS/INS integration. Under such an arrangement, we derive the error dynamics of the system and develop a Kalman Filter for estimating the errors in position and attitude. Using a control-based approach to observability, we show that the errors in both position and attitude (including yaw) are fully observable when there is a component of acceleration perpendicular to the velocity vector in the navigation frame. Numerical simulations are performed to confirm the observability analysis.
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It is possible for the visual attention characteristics of a person to be exploited as a biometric for authentication or identification of individual viewers. The visual attention characteristics of a person can be easily monitored by tracking the gaze of a viewer during the presentation of a known or unknown visual scene. The positions and sequences of gaze locations during viewing may be determined by overt (conscious) or covert (sub-conscious) viewing behaviour. This paper presents a method to authenticate individuals using their covert viewing behaviour, thus yielding a unique behavioural biometric. A method to quantify the spatial and temporal patterns established by the viewer for their covert behaviour is proposed utilsing a principal component analysis technique called `eigenGaze'. Experimental results suggest that it is possible to capture the unique visual attention characteristics of a person to provide a simple behavioural biometric.
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The antiretroviral therapy (ART) program for People Living with HIV/AIDS (PLHIV) in Vietnam has been scaled up rapidly in recent years (from 50 clients in 2003 to almost 38,000 in 2009). ART success is highly dependent on the ability of the patients to fully adhere to the prescribed treatment regimen. Despite the remarkable extension of ART programs in Vietnam, HIV/AIDS program managers still have little reliable data on levels of ART adherence and factors that might promote or reduce adherence. Several previous studies in Vietnam estimated extremely high levels of ART adherence among their samples, although there are reasons to question the veracity of the conclusion that adherence is nearly perfect. Further, no study has quantitatively assessed the factors influencing ART adherence. In order to reduce these gaps, this study was designed to include several phases and used a multi-method approach to examine levels of ART non-adherence and its relationship to a range of demographic, clinical, social and psychological factors. The study began with an exploratory qualitative phase employing four focus group discussions and 30 in-depth interviews with PLHIV, peer educators, carers and health care providers (HCPs). Survey interviews were completed with 615 PLHIV in five rural and urban out-patient clinics in northern Vietnam using an Audio Computer Assisted Self-Interview (ACASI) and clinical records extraction. The survey instrument was carefully developed through a systematic procedure to ensure its reliability and validity. Cultural appropriateness was considered in the design and implementation of both the qualitative study and the cross sectional survey. The qualitative study uncovered several contrary perceptions between health care providers and HIV/AIDS patients regarding the true levels of ART adherence. Health care providers often stated that most of their patients closely adhered to their regimens, while PLHIV and their peers reported that “it is not easy” to do so. The quantitative survey findings supported the PLHIV and their peers’ point of view in the qualitative study, because non-adherence to ART was relatively common among the study sample. Using the ACASI technique, the estimated prevalence of onemonth non-adherence measured by the Visual Analogue Scale (VAS) was 24.9% and the prevalence of four-day not-on-time-adherence using the modified Adult AIDS Clinical Trials Group (AACTG) instrument was 29%. Observed agreement between the two measures was 84% and kappa coefficient was 0.60 (SE=0.04 and p<0.0001). The good agreement between the two measures in the current study is consistent with those found in previous research and provides evidence of cross-validation of the estimated adherence levels. The qualitative study was also valuable in suggesting important variables for the survey conceptual framework and instrument development. The survey confirmed significant correlations between two measures of ART adherence (i.e. dose adherence and time adherence) and many factors identified in the qualitative study, but failed to find evidence of significant correlations of some other factors and ART adherence. Non-adherence to ART was significantly associated with untreated depression, heavy alcohol use, illicit drug use, experiences with medication side-effects, chance health locus of control, low quality of information from HCPs, low satisfaction with received support and poor social connectedness. No multivariate association was observed between ART adherence and age, gender, education, duration of ART, the use of adherence aids, disclosure of ART, patients’ ability to initiate communication with HCPs or distance between clinic and patients’ residence. This is the largest study yet reported in Asia to examine non-adherence to ART and its possible determinants. The evidence strongly supports recent calls from other developing nations for HIV/AIDS services to provide screening, counseling and treatment for patients with depressive symptoms, heavy use of alcohol and substance use. Counseling should also address fatalistic beliefs about chance or luck determining health outcomes. The data suggest that adherence could be enhanced by regularly providing information on ART and assisting patients to maintain social connectedness with their family and the community. This study highlights the benefits of using a multi-method approach in examining complex barriers and facilitators of medication adherence. It also demonstrated the utility of the ACASI interview method to enhance open disclosure by people living with HIV/AIDS and thus, increase the veracity of self-reported data.
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In this paper, we present a method for the recovery of position and absolute attitude (including pitch, roll and yaw) using a novel fusion of monocular Visual Odometry and GPS measurements in a similar manner to a classic loosely-coupled GPS/INS error state navigation filter. The proposed filter does not require additional restrictions or assumptions such as platform-specific dynamics, map-matching, feature-tracking, visual loop-closing, gravity vector or additional sensors such as an IMU or magnetic compass. An observability analysis of the proposed filter is performed, showing that the scale factor, position and attitude errors are fully observable under acceleration that is non-parallel to velocity vector in the navigation frame. The observability properties of the proposed filter are demonstrated using numerical simulations. We conclude the article with an implementation of the proposed filter using real flight data collected from a Cessna 172 equipped with a downwards-looking camera and GPS, showing the feasibility of the algorithm in real-world conditions.
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This article presents a visual servoing system to follow a 3D moving object by a Micro Unmanned Aerial Vehicle (MUAV). The presented control strategy is based only on the visual information given by an adaptive tracking method based on the colour information. A visual fuzzy system has been developed for servoing the camera situated on a rotary wing MAUV, that also considers its own dynamics. This system is focused on continuously following of an aerial moving target object, maintaining it with a fixed safe distance and centred on the image plane. The algorithm is validated on real flights on outdoors scenarios, showing the robustness of the proposed systems against winds perturbations, illumination and weather changes among others. The obtained results indicate that the proposed algorithms is suitable for complex controls task, such object following and pursuit, flying in formation, as well as their use for indoor navigation
Resumo:
Objective The current study evaluated part of the Multifactorial Model of Driving Safety to elucidate the relative importance of cognitive function and a limited range of standard measures of visual function in relation to the Capacity to Drive Safely. Capacity to Drive Safely was operationalized using three validated screening measures for older drivers. These included an adaptation of the well validated Useful Field of View (UFOV) and two newer measures, namely a Hazard Perception Test (HPT), and a Hazard Change Detection Task (HCDT). Method Community dwelling drivers (n = 297) aged 65–96 were assessed using a battery of measures of cognitive and visual function. Results Factor analysis of these predictor variables yielded factors including Executive/Speed, Vision (measured by visual acuity and contrast sensitivity), Spatial, Visual Closure, and Working Memory. Cognitive and Vision factors explained 83–95% of age-related variance in the Capacity to Drive Safely. Spatial and Working Memory were associated with UFOV, HPT and HCDT, Executive/Speed was associated with UFOV and HCDT and Vision was associated with HPT. Conclusion The Capacity to Drive Safely declines with chronological age, and this decline is associated with age-related declines in several higher order cognitive abilities involving manipulation and storage of visuospatial information under speeded conditions. There are also age-independent effects of cognitive function and vision that determine driving safety.
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We present an iterative hierarchical algorithm for multi-view stereo. The algorithm attempts to utilise as much contextual information as is available to compute highly accurate and robust depth maps. There are three novel aspects to the approach: 1) firstly we incrementally improve the depth fidelity as the algorithm progresses through the image pyramid; 2) secondly we show how to incorporate visual hull information (when available) to constrain depth searches; and 3) we show how to simultaneously enforce the consistency of the depth-map by continual comparison with neighbouring depth-maps. We show that this approach produces highly accurate depth-maps and, since it is essentially a local method, is both extremely fast and simple to implement.