389 resultados para Asynchronous vision sensor
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This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.
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This paper presents large, accurately calibrated and time-synchronised datasets, gathered outdoors in controlled environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. It discusses how the data collection process was designed, the conditions in which these datasets have been gathered, and some possible outcomes of their exploitation, in particular for the evaluation of performance of sensors and perception algorithms for UGVs.
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This document describes large, accurately calibrated and time-synchronised datasets, gathered in controlled environmental conditions, using an unmanned ground vehicle equipped with a wide variety of sensors. These sensors include: multiple laser scanners, a millimetre wave radar scanner, a colour camera and an infra-red camera. Full details of the sensors are given, as well as the calibration parameters needed to locate them with respect to each other and to the platform. This report also specifies the format and content of the data, and the conditions in which the data have been gathered. The data collection was made in two different situations of the vehicle: static and dynamic. The static tests consisted of sensing a fixed ’reference’ terrain, containing simple known objects, from a motionless vehicle. For the dynamic tests, data were acquired from a moving vehicle in various environments, mainly rural, including an open area, a semi-urban zone and a natural area with different types of vegetation. For both categories, data have been gathered in controlled environmental conditions, which included the presence of dust, smoke and rain. Most of the environments involved were static, except for a few specific datasets which involve the presence of a walking pedestrian. Finally, this document presents illustrations of the effects of adverse environmental conditions on sensor data, as a first step towards reliability and integrity in autonomous perceptual systems.
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Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.
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In this paper we present large, accurately calibrated and time-synchronized data sets, gathered outdoors in controlled and variable environmental conditions, using an unmanned ground vehicle (UGV), equipped with a wide variety of sensors. These include four 2D laser scanners, a radar scanner, a color camera and an infrared camera. It provides a full description of the system used for data collection and the types of environments and conditions in which these data sets have been gathered, which include the presence of airborne dust, smoke and rain.
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Purpose To investigate the differences between and variations across time in corneal topography and ocular wavefront aberrations in young Singaporean myopes and emmetropes. Methods We used a videokeratoscope and wavefront sensor to measure the ocular surface topography and wavefront aberrations of the total eye optics in the morning, mid-day and late afternoon on two separate days. Topography data were used to derive the corneal surface wavefront aberrations. Both the corneal and total wavefronts were analysed up to the 4th radial order of the Zernike polynomial expansion, and were centred on the entrance pupil (5 mm). The participants included 12 young progressing myopes, 13 young stable myopes and 15 young age-matched emmetropes. Results For all subjects considered together there were significant changes in some of the aberrations terms across the day, such as spherical aberration ( ) and vertical coma ( ) (repeated measures ANOVA, p<0.05). The magnitude of positive spherical aberration ( ) was significantly lower in the progressing myope group than that of the stable myopes (p=0.04) and emmetrope group (p=0.02). There were also significant interactions between refractive group and time of day for with/against-the-rule astigmatism ( ). Significantly lower 4th order RMS of ocular wavefront aberrations were found in the progressing myope group compared with the stable myopes and emmetropes (p<0.01). Conclusions These differences and variations in the corneal and total aberrations may have significance for our understanding of refractive error development and for clinical applications requiring accurate wavefront measurements.
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Bridges are important infrastructures of all nations and are required for transportation of goods as well as human. A catastrophic failure can result in loss of lives and enormous financial hardship to the nation. Although various kinds of sensors are now available to monitor the health of the structures due to corrosion, they do not provide permanent and long term measurements. This paper investigates the fabrication of Carbon Nanotube (CNT) based composite sensors for corrosion detection of structures. Multi-wall CNT (MWCNT)/Nafion composite sensors were fabricated to evaluate their electrical properties for corrosion detection. The test specimens were subjected to real life corrosion experimental tests and the results confirm that the electrical resistance of the sensor electrode was dramatically changed due to corrosion.
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This paper describes a novel Autonomous Surface Vehicle capable of navigating throughout complex inland water storages and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran can collect this information throughout the water column whilst the vehicle is moving. A unique feature of this ASV is its integration into a storage scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper provides an overview of the vehicle design and operation including control, laser-based obstacle avoidance, and vision-based inspection capabilities. Experimental results are shown illustrating its ability to continuously collect key water quality parameters and compliment intensive manual monitoring campaigns.
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The operation of Autonomous Underwater Vehicles (AUVs) within underwater sensor network fields provides an opportunity to reuse the network infrastructure for long baseline localisation of the AUV. Computationally efficient localisation can be accomplished using off-the-shelf hardware that is comparatively inexpensive and which could already be deployed in the environment for monitoring purposes. This paper describes the development of a particle filter based localisation system which is implemented onboard an AUV in real-time using ranging information obtained from an ad-hoc underwater sensor network. An experimental demonstration of this approach was conducted in a lake with results presented illustrating network communication and localisation performance.
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We present a pole inspection system for outdoor environments comprising a high-speed camera on a vertical take-off and landing (VTOL) aerial platform. The pole inspection task requires a vehicle to fly close to a structure while maintaining a fixed stand-off distance from it. Typical GPS errors make GPS-based navigation unsuitable for this task however. When flying outdoors a vehicle is also affected by aerodynamics disturbances such as wind gusts, so the onboard controller must be robust to these disturbances in order to maintain the stand-off distance. Two problems must therefor be addressed: fast and accurate state estimation without GPS, and the design of a robust controller. We resolve these problems by a) performing visual + inertial relative state estimation and b) using a robust line tracker and a nested controller design. Our state estimation exploits high-speed camera images (100Hz) and 70Hz IMU data fused in an Extended Kalman Filter (EKF). We demonstrate results from outdoor experiments for pole-relative hovering, and pole circumnavigation where the operator provides only yaw commands. Lastly, we show results for image-based 3D reconstruction and texture mapping of a pole to demonstrate the usefulness for inspection tasks.
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In this paper, we introduce a vision called Smart Material Interfaces (SMIs), which takes advantage of the latest generation of engineered materials that has a special property defined “smart”. They are capable of changing their physical properties, such as shape, size and color, and can be controlled by using certain stimuli (light, potential difference, temperature and so on). We describe SMIs in relation to Tangible User Interfaces (TUIs) to convey the usefulness and a better understanding of SMIs.
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This research investigated the prevalence of vision disorders in Queensland Indigenous primary school children, creating the first comprehensive visual profile of Indigenous children. Findings showed reduced convergence ability and reduced visual information processing skills were more common in Indigenous compared to non-Indigenous children. Reduced visual information processing skills were also associated with reduced reading outcomes in both groups of children. As early detection of visual disorders is important, the research also reviewed the delivery of screening programs across Queensland and proposed a model for improved coordination and service delivery of vision screening to Queensland school children.
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PURPOSE To investigate changes in the characteristics of the corneal optics, total optics, anterior biometrics and axial length of the eye during a near task, in downward gaze, over 10 min. METHODS Ten emmetropes (mean - 0.14 ± 0.24 DS) and 10 myopes (mean - 2.26 ± 1.42 DS) aged from 18 to 30 years were recruited. To measure ocular biometrics and corneal topography in downward gaze, an optical biometer (Lenstar LS900) and a rotating Scheimpflug camera (Pentacam HR) were inclined on a custom built, height and tilt adjustable table. The total optics of the eye were measured in downward gaze with binocular fixation using a modified Shack-Hartmann wavefront sensor. Initially, subjects performed a distance viewing task at primary gaze for 10 min to provide a "wash-out" period for prior visual tasks. A distance task (watching video at 6 m) in downward gaze (25°) and a near task (watching video on a portable LCD screen with 2.5 D accommodation demand) in primary gaze and 25°downward gaze were then carried out, each for 10 min in a randomized order. During measurements, in dichoptic view, a Maltese cross was fixated with the right (untested) eye and the instrument’s fixation target was fixated with the subject’s tested left eye. Immediately after (0 min), 5 and 10 min from the commencement of each trial, measurements of ocular parameters were acquired in downward gaze. RESULTS Axial length exhibited a significant increase with downward gaze and accommodation over time (p<0.05). The greatest axial elongation was observed in downward gaze with 2.5 D accommodation after 10 min (mean change from baseline 23±3 µm). Downward gaze also caused greater changes in anterior chamber depth (ACD) and lens thickness (LT) with accommodation (ACD mean change -163±12µm at 10 min; LT mean change 173±17 µm at 10 min) compared to primary gaze with accommodation (ACD mean change -138±12µm at 10 min; LT mean change 131±15 µm at 10 min). Both corneal power and total ocular power changed by a small but significant amount with downward gaze (p<0.05), resulting in a myopic shift (~0.10 D) in the spherical power of the eye compared with primary gaze. CONCLUSION The axial length, anterior biometrics and ocular refraction change significantly with accommodation in downward gaze as a function of time. These findings provide new insights into the optical and bio-mechanical changes of the eye during typical near tasks.
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In a conventional ac motor drive using field-oriented control, a dc-link voltage, speed, and at least two current sensors are required. Hence, in the event of sensor failure, the performance of the drive system can be severely compromised. This paper presents a sensor fault-tolerant control strategy for interior permanent-magnet synchronous motor (IPMSM) drives. Three independent observers are proposed to estimate the speed, dc-link voltage, and currents of the machine. If a sensor fault is detected, the drive system isolates the faulty sensor while retaining the remaining functional ones. The signal is then acquired from the corresponding observer in order to maintain the operation of the drive system. The experimental results provided verify the effectiveness of the proposed approach.
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Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.