45,275 research outputs found
Keyframe-based monocular SLAM: design, survey, and future directions
Extensive research in the field of monocular SLAM for the past fifteen years
has yielded workable systems that found their way into various applications in
robotics and augmented reality. Although filter-based monocular SLAM systems
were common at some time, the more efficient keyframe-based solutions are
becoming the de facto methodology for building a monocular SLAM system. The
objective of this paper is threefold: first, the paper serves as a guideline
for people seeking to design their own monocular SLAM according to specific
environmental constraints. Second, it presents a survey that covers the various
keyframe-based monocular SLAM systems in the literature, detailing the
components of their implementation, and critically assessing the specific
strategies made in each proposed solution. Third, the paper provides insight
into the direction of future research in this field, to address the major
limitations still facing monocular SLAM; namely, in the issues of illumination
changes, initialization, highly dynamic motion, poorly textured scenes,
repetitive textures, map maintenance, and failure recovery
Comparison of Five Spatio-Temporal Satellite Image Fusion Models over Landscapes with Various Spatial Heterogeneity and Temporal Variation
In recent years, many spatial and temporal satellite image fusion (STIF) methods have been developed to solve the problems of trade-off between spatial and temporal resolution of satellite sensors. This study, for the first time, conducted both scene-level and local-level comparison of five state-of-art STIF methods from four categories over landscapes with various spatial heterogeneity and temporal variation. The five STIF methods include the spatial and temporal adaptive reflectance fusion model (STARFM) and Fit-FC model from the weight function-based category, an unmixing-based data fusion (UBDF) method from the unmixing-based category, the one-pair learning method from the learning-based category, and the Flexible Spatiotemporal DAta Fusion (FSDAF) method from hybrid category. The relationship between the performances of the STIF methods and scene-level and local-level landscape heterogeneity index (LHI) and temporal variation index (TVI) were analyzed. Our results showed that (1) the FSDAF model was most robust regardless of variations in LHI and TVI at both scene level and local level, while it was less computationally efficient than the other models except for one-pair learning; (2) Fit-FC had the highest computing efficiency. It was accurate in predicting reflectance but less accurate than FSDAF and one-pair learning in capturing image structures; (3) One-pair learning had advantages in prediction of large-area land cover change with the capability of preserving image structures. However, it was the least computational efficient model; (4) STARFM was good at predicting phenological change, while it was not suitable for applications of land cover type change; (5) UBDF is not recommended for cases with strong temporal changes or abrupt changes. These findings could provide guidelines for users to select appropriate STIF method for their own applications
Towards Flight Trials for an Autonomous UAV Emergency Landing using Machine Vision
This paper presents the evolution and status of a number of research programs focussed on developing an automated fixed wing UAV landing system. Results obtained in each of the three main areas of research as vision-based site identification, path and trajectory planning and multi-criteria decision making are presented. The results obtained provide a baseline for further refinements and constitute the starting point for the implementation of a prototype system ready for flight testing
Commercialisation of precision agriculture technologies in the macadamia industry
A prototype vision-based yield monitor has been developed for the macadamia industry. The system estimates yield for individual trees by detecting nuts and their harvested location. The technology was developed by the National Centre for Engineering in Agriculture, University of Southern Queensland for the purpose of reducing labour and costs in varietal assessment trials where yield for individual trees are required to be measured to indicate tree performance. The project was commissioned by Horticulture Australia Limited
Programmable Logic Devices in Experimental Quantum Optics
We discuss the unique capabilities of programmable logic devices (PLD's) for
experimental quantum optics and describe basic procedures of design and
implementation. Examples of advanced applications include optical metrology and
feedback control of quantum dynamical systems. As a tutorial illustration of
the PLD implementation process, a field programmable gate array (FPGA)
controller is used to stabilize the output of a Fabry-Perot cavity
Dual-frequency GPS survey for validation of a regional DTM and for the generation of local DTM data for sea-level rise modelling in an estuarine salt marsh
Global average temperatures have risen by an average of 0.07°C per decade over the last
100 years, with a warming trend of 0.13°C per decade over the last 50 years.
Temperatures are predicted to rise by 2°C - 4.4°C by 2100 leading to global average sealevel
rise (SLR) of 2 – 6mm per year (20 – 60cms in total) up to 2100 (IPCC 2007) with
impacts for protected coastal habitats in Ireland.
Estuaries are predominantly sedimentary environments, and are characterised by shallow
coastal slope gradients, making them sensitive to even modest changes in sea-level. The
Shannon estuary is the largest river estuary in Ireland and is designated as a Special Area
of Conservation (SAC) under the EU Habitats Directive (EU 1992) providing protection
for listed habitats within it, including estuarine salt marsh.
Trends in Shannon estuary tidal data from 1877 – 2004 suggest an average upward SLR
trend of 4 - 5mm/yr over this period. A simple linear extension of this historical trend
would imply that local SLR will be in the region of 40 - 45cm by 2100. However, this
may underestimate actual SLR for the estuary by 2100, since it takes no account of
predicted climate-driven global SLR acceleration (IPCC 2007) up to 2100
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