Using image quality metrics to detect smoke-affected laser data

Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.

Laser-camera data discrepancies and reliable perception in outdoor robotics

This work aims to promote integrity in autonomous perceptual systems, with a focus on outdoor unmanned ground vehicles equipped with a camera and a 2D laser range finder. A method to check for inconsistencies between the data provided by these two heterogeneous sensors is proposed and discussed. First, uncertainties in the estimated transformation between the laser and camera frames are evaluated and propagated up to the projection of the laser points onto the image. Then, for each pair of laser scan-camera image acquired, the information at corners of the laser scan is compared with the content of the image, resulting in a likelihood of correspondence. The result of this process is then used to validate segments of the laser scan that are found to be consistent with the image, while inconsistent segments are rejected. Experimental results illustrate how this technique can improve the reliability of perception in challenging environmental conditions, such as in the presence of airborne dust.

Histogram matching and global initialization for laser-only SLAM in large unstructured environments

This paper presents an enhanced algorithm for matching laser scan maps using histogram correlations. The histogram representation effectively summarizes a map's salient features such that pairs of maps can be matched efficiently without any prior guess as to their alignment. The histogram matching algorithm has been enhanced in order to work well in outdoor unstructured environments by using entropy metrics, weighted histograms and proper thresholding of quality metrics. Thus our large-scale scan-matching SLAM implementation has a vastly improved ability to close large loops in real-time even when odometry is not available. Our experimental results have demonstrated a successful mapping of the largest area ever mapped to date using only a single laser scanner. We also demonstrate our ability to solve the lost robot problem by localizing a robot to a previously built map without any prior initialization.

Blackcloud

The work was derived from terrestrial laser scan data of a bio-diverse landscape on the SE coast of Western Australia. The digital three dimensional scan data has been converged and then a portion of that computer aided design (CAD) file has been captured via ‘screen capture’ to produce Blackcloud.---------- The primary intention behind the production of the work was to expand understanding on the means of representing and then designing for sites in ‘kwongan’ landscapes which are constituted by highly biodiverse, bushfire prone heath vegetation.

Before and after the fire

The work was derived from terrestrial laser scan data of a bio-diverse landscape on the SE coast of Western Australia. The scanning was conducted both before and after a significant bushfire event. The digital three dimensional scan data has been converged and then abstracted into a two dimensional vertical sections or slice which reveals the vegetal surface of heath vegetation and the surface of the landform.---------- This abstraction converts the complex data into spatial information so that it is meaningful in the context the architectural and landscape architectural design process. The primary intention behind the production of the work was to expand understanding on the means of representing and then designing for sites in ‘kwongan’ landscapes which are constituted by highly biodiverse, bushfire prone heath vegetation.

Heathsections

The work was derived from terrestrial laser scan data of a bio-diverse landscape on the SE coast of Western Australia. The three dimensional scan data has been abstracted into two dimensional side sections or slices – in a manner which converts the complex data into spatial information which is meaningful in the context of the act of architectural and landscape architectural design. The primary intention behind the production of the work was to expand understanding on the means of representation of ‘kwongan’ landscapes which are constituted by highly biodiverse - and thus difficult to measure - heath vegetation.

Horizonal

Horizonal was derived from terrestrial laser scan data of a bio-diverse landscape on the SE coast of Western Australia. The digital three dimensional scan data has been converged with geospatial survey of the landform captured through RTKGPS survey technology. Also incorporated into the image is a series of photographs taken using a photogrammetric technique wherein the position and view angle of each photograph is measured relative to a geographic datum point. The primary intention behind the production of the work was to expand understandings on the relationship between scenic photography and geospatial maps of remote, bio-diverse landscapes which are experiencing urban development for the first time.

Heathprint

The work was derived from terrestrial laser scan data of a bio-diverse landscape on the SE coast of Western Australia. The digital three dimensional scan data has been abstracted into two dimensional horizontal sections or slices. This abstraction converts the complex data into spatial information which is meaningful in the context of the act of architectural and landscape architectural design. The primary intention behind the production of the work was to expand understanding on the means of representing and then designing for sites in 'kwongan' landscapes which are constituted by highly biodiverse - and thus difficult to measure - heath vegetation. From Heathprint the author generated contour intervals of the landform upon which an associate (Daniela Simon architect) designed a work of architecture, which subsequently was awarded a commendation for residential architecture in the WA Chapter Australia Institute of Architects awards 2007.

Towards automated and in-situ, near-real time 3-D reconstruction of coral reef environments

Coral reefs are biologically complex ecosystems that support a wide variety of marine organisms. These are fragile communities under enormous threat from natural and human-based influences. Properly assessing and measuring the growth and health of reefs is essential to understanding impacts of ocean acidification, coastal urbanisation and global warming. In this paper, we present an innovative 3-D reconstruction technique based on visual imagery as a non-intrusive, repeatable, in situ method for estimating physical parameters, such as surface area and volume for efficient assessment of long-term variability. The reconstruction algorithms are presented, and benchmarked using an existing data set. We validate the technique underwater, utilising a commercial-off-the-shelf camera and a piece of staghorn coral, Acropora cervicornis. The resulting reconstruction is compared with a laser scan of the coral piece for assessment and validation. The comparison shows that 77% of the pixels in the reconstruction are within 0.3 mm of the ground truth laser scan. Reconstruction results from an unknown video camera are also presented as a segue to future applications of this research.

Laser doppler imaging in a paediatric burns population

Objective Laser Doppler imaging (LDI) was compared to wound outcomes in children's burns, to determine if the technology could be used to predict these outcomes. Methods Forty-eight patients with a total of 85 burns were included in the study. Patient median age was 4 years 10 months and scans were taken 0–186 h post-burn using the fast, low-resolution setting on the Moor LDI2 laser Doppler imager. Wounds were managed by standard practice, without taking into account the scan results. Time until complete re-epithelialisation and whether or not grafting and scar management were required were recorded for each wound. If wounds were treated with Silvazine™ or Acticoat™ prior to the scan, this was also recorded. Results The predominant colour of the scan was found to be significantly related to the re-epithelialisation, grafting and scar management outcomes and could be used to predict those outcomes. The prior use of Acticoat™ did not affect the scan relationship to outcomes, however, the use of Silvazine™ did complicate the relationship for light blue and green scanned partial thickness wounds. Scans taken within the 24-h window after-burn also appeared to be accurate predictors of wound outcome. Conclusion Laser Doppler imaging is accurate and effective in a paediatric population with a low-resolution fast-scan.

Efficiently capturing large, complex cultural heritage sites with a handheld mobile 3D laser mapping system

Accurate three-dimensional representations of cultural heritage sites are highly valuable for scientific study, conservation, and educational purposes. In addition to their use for archival purposes, 3D models enable efficient and precise measurement of relevant natural and architectural features. Many cultural heritage sites are large and complex, consisting of multiple structures spatially distributed over tens of thousands of square metres. The process of effectively digitising such geometrically complex locations requires measurements to be acquired from a variety of viewpoints. While several technologies exist for capturing the 3D structure of objects and environments, none are ideally suited to complex, large-scale sites, mainly due to their limited coverage or acquisition efficiency. We explore the use of a recently developed handheld mobile mapping system called Zebedee in cultural heritage applications. The Zebedee system is capable of efficiently mapping an environment in three dimensions by continually acquiring data as an operator holding the device traverses through the site. The system was deployed at the former Peel Island Lazaret, a culturally significant site in Queensland, Australia, consisting of dozens of buildings of various sizes spread across an area of approximately 400 × 250 m. With the Zebedee system, the site was scanned in half a day, and a detailed 3D point cloud model (with over 520 million points) was generated from the 3.6 hours of acquired data in 2.6 hours. We present results demonstrating that Zebedee was able to accurately capture both site context and building detail comparable in accuracy to manual measurement techniques, and at a greatly increased level of efficiency and scope. The scan allowed us to record derelict buildings that previously could not be measured because of the scale and complexity of the site. The resulting 3D model captures both interior and exterior features of buildings, including structure, materials, and the contents of rooms.