Arnold Bauer

Mass Movement Monitoring Using Terrestrial Laser Scanner for Rock Fall Management

The danger of a rock fall or rockslide event is omnipresent, mainly due to dense settlement, excessive land usage even in alpine regions, and the global warming. In the case of a rock fall event the rapid operational availability of a measurement system is important for disaster management to assess the risk and to take appropriate measures.

Algorithmic solution for autonomous vision-based off-road navigation

A vision based navigation system is a basic tool to provide autonomous operations of unmanned vehicles. For offroad navigation that means that the vehicle equipped with a stereo vision system and perhaps a laser ranging device shall be able to maintain a high level of autonomy under various illumination conditions and with little a priori information about the underlying scene. The task becomes particularly important for unmanned planetary exploration with the help of autonomous rovers. For example in the LEDA Moon exploration project currently under focus by the European Space Agency (ESA), during the autonomous mode the vehicle (rover) should perform the following operations: on-board absolute localization, elevation model (DEM) generation, obstacle detection and relative localization, global path planning and execution. Focus of this article is a computational solution for fully autonomous path planning and path execution. An operational DEM generation method based on stereoscopy is introduced. Self-localization on the DEM and robust natural feature tracking are used as basic navigation steps, supported by inertial sensor systems. The following operations are performed on the basis of stereo image sequences: 3D scene reconstruction, risk map generation, local path planning, camera position update during the motion on the basis of landmarks tracking, obstacle avoidance. Experimental verification is done with the help of a laboratory terrain mockup and a high precision camera mounting device. It is shown that standalone tracking using automatically identified landmarks is robust enough to give navigation data for further stereoscopic reconstruction of the surrounding terrain. Iterative tracking and reconstruction leads to a complete description of the vehicle path and its surrounding with an accuracy high enough to meet the specifications for autonomous outdoor navigation.

Photogrammetric fingerprint unwrapping

Abstract Fingerprints are important biometric cues. Compared to conventional fingerprint sensors the use of contact-free stereoscopic image acquisition of the front-most finger segment has a set of advantages: Finger deformation is avoided, the entire relevant area for biometric use is covered, some technical aspects like sensor maintenance and cleaning are facilitated, and access to a three-dimensional reconstruction of the covered area is possible. We describe a photogrammetric workflow for nail-to-nail fingerprint reconstruction: A calibrated sensor setup with typically 5 cameras and dedicated illumination acquires adjacent stereo pairs. Using the silhouettes of the segmented finger a raw cylindrical model is generated. After preprocessing (shading correction, dust removal, lens distortion correction), each individual camera texture is projected onto the model. Image-to-image matching on these pseudo ortho images and dense 3D reconstruction obtains a textured cylindrical digital surface model with radial distances around the major axis and a grid size in the range of 25–50 µm. The model allows for objective fingerprint unwrapping and novel fingerprint matching algorithms since 3D relations between fingerprint features are available as additional cues. Moreover, covering the entire region with relevant fingerprint texture is particularly important for establishing a comprehensive forensic database. The workflow has been implemented in portable C and is ready for industrial exploitation. Further improvement issues are code optimization, unwrapping method, illumination strategy to avoid highlights and to improve the initial segmentation, and the comparison of the unwrapping result to conventional fingerprint acquisition technology.

Stereo reconstruction from dense disparity maps using the locus method

The reconstruction of a surface having already matched corresponding points from stereo images (disparities) is a nontrivial task. This paper presents a new technique, the so-called Locus method, that exploits sensor geometry to efficiently build a terrain representation from stereo disparities. The power of this approach is the efficient and direct computation of a dense elevation map in arbitrary resolution. Additionally it proposes to solve problems like occlusions, ambiguities, and uncertainties caused by stereo matching errors. We extended the Locus method for active range finder data to the stereo disparity mapping case. For this reason, a newly developed fast matching method is utilized that provides dense disparity maps, hence a disparity for each input pixel. Once this data set is given, the Locus method can be applied in a straightforward and efficient way to gain a robust 3D reconstruction of the observed surface. It operates directly in image space, using dense and uniform measurements instead of first converting to object space. Experiments on synthetic and natural environment data show that the Locus method is less sensitive to disparity noise than traditional reconstruction.

Vision-Based Terrestrial Surface Monitoring

The monitoring of geo-risk areas is getting more and more importance due to increasing damage caused by hazardous events such as rock slides, as a result of the environmental change. Terrestrial long-range sensing (up to several kilometres of distance between sensor and target region) is a valuable means for monitoring such sites using non-signalized targets in high resolution, which is necessary to detect regions, amount, direction and trends of motion early enough to take risk mitigation measures. The technology to realize such a sensing strategy combines various fields of research, such as sensor technology, surveying, computer vision and geological sciences. This chapter describes two vision-based sensing techniques suited for terrestrial surface monitoring (terrestrial laser scanning, and image-based tacheometers), and their sensing strategies, data processing and data exploitation issues. Examples for monitoring frameworks are given, and technical and engineering solutions are described. A set of applications from permafrost, glacier and snow cover monitoring, as well as rock fall site monitoring shows the relevance, technologic maturity and limits of existing approaches. Rock falls and other geo-hazards being the major fields of application for such systems, the chances of saving lives, protecting infrastructure and habitats and avoiding injury to field personnel are increased so that the better and more accurate event can be monitored. The research and technology described in this chapter will help the surveying, photogrammetry and computer vision community fighting global warming impacts.

Cavity surface measuring system using stereo reconstruction

3D reconstruction of highly textured surfaces on unvegetated terrain is of major interest for stereo vision based mapping applications. We describe a prototype system for automatic modeling of such scenes. It is based on two frame CCD cameras, which are tightly attached to each other ensuring constant relative orientation. One camera is used to acquire known reference points to get the exterior orientation of the system, the other records the surface images. The system is portable to keep image acquisition as short as possible. Automatic calibration using the images acquired by the calibration camera permits the computation of exterior orientation parameters of the surface camera via a transformation matrix. A robust matching method providing dense disparities together with a flexible reconstruction algorithm renders an accurate grid of 3D points on arbitrarily shaped surfaces. The results of several stereo reconstructions are merged. Projection onto the global shape allows easy evaluation of volumes, and thematic mapping with respect to the desired surface geometry in construction processes. We report on accuracy and emphasize on the practical usage. It is shown that the prototpye system is able to generate a proper data set of surface descriptions that is accurate and dense enough to serve as documentation, planning and accounting basis.

Near-range stereo for Mars landing site reconstruction

Within the European Mars Express Mission to be launched 2003 the Beagle2 Lander will foresee the access to stereoscopic views of the surrounding Martian surface after touchdown. For scientific purposes the necessity for a high resolution three dimensional (3D) reconstruction of the landing site is evident. A lander vision subsystem capable of reconstructing the landing site and its vicinity using a stereo camera mounted on the robotic arm of the lander is used therefore. Knowledge about the geometric camera features (position and pointing with respect to each other, position and pointing with respect to the lander, intrinsic parameters and lens distortion) are determined in a calibration step on ground before takeoff. The 3D reconstruction of the landing site is performed after landing by means of stereo matching using the transmitted images. Merging several stereo reconstructions uses the respective robotic arm states during image acquisition for calibration. This paper describes the full processing chain consisting of calibration of the sensor system, stereo matching, 3D reconstruction and merging of results. Emphasis is laid on the stereo reconstruction step. A software system configuration is proposed. Tests using Mars Pathfinder images as example data show the feasibility of the approach and give accuracy estimations.

Geological Analysis of Martian Rover‐Derived Digital Outcrop Models Using the 3‐D Visualization Tool, Planetary Robotics 3‐D Viewer—PRo3D

Panoramic camera systems on robots exploring the surface of Mars are used to collect images of terrain and rock outcrops which they encounter along their traverse. Image mosaics from these cameras are essential in mapping the surface geology and selecting locations for analysis by other instruments on the rover’s payload. 2-D images do not truly portray the depth of field of features within an image, nor their 3-D geometry. This paper describes a new 3-D visualization software tool for geological analysis of Martian rover-derived Digital Outcrop Models created using photogrammetric processing of stereo-images using the Planetary Robotics Vision Processing tool developed for 3-D vision processing of ExoMars PanCam and Mars 2020 Mastcam-Z data. Digital Outcrop Models are rendered in real time in the Planetary Robotics 3-D Viewer PRo3D, allowing scientists to roam outcrops as in a terrestrial field campaign. Digitization of point, line, and polyline features is used for measuring the physical dimensions of geological features and communicating interpretations. Dip and strike of bedding and fractures is measured by digitizing a polyline along the contact or fracture trace, through which a best fit plane is plotted. The attitude of this plane is calculated in the software. Here we apply these tools to analysis of sedimentary rock outcrops and quantification of the geometry of fracture systems encountered by the science teams of NASA’s Mars Exploration Rover Opportunity and Mars Science Laboratory rover Curiosity. We show the benefits PRo3D allows for visualization and collection of geological interpretations and analyses from rover-derived stereo-images. Plain Language Summary Key data returned from robots exploring the surface of Mars are the images they take of the landscape and rock formations. These are sent back to Earth for detailed investigation and analysis by the science teams. It is difficult to collect reliable measurements from photographs, as they do not truly represent the three-dimensionality of the features within them. In this paper, we present a new 3-D visualization software tool, PRo3D, which enables visualization of 3-D digital models of rock outcrops imaged by robots exploring the surface of Mars. These 3-D models are constructed from mosaicked photographs taken by the stereo panoramic cameras which are positioned on a mast on the rover. This provides a huge advantage to scientists who want to study and analyze the terrain and geology of exposed rock outcrops which surround the rover. Here we apply the tools available in PRo3D to sedimentological and structural analysis of 3-D Digital Outcrop Models of four areas explored by the Mars Exploration Rover Opportunity and Mars Science Laboratory Curiosity rover science teams and show that this method of 3-D visualization and analysis allows scientists to carry out important procedures that would be conducted in a terrestrial field geology campaign.

Monitoring snow avalanche terrain with Automated Terrestrial Laser Scanning

In the scope of the presented work, an Automated Terrestrial Laser Scanner (ATLS) was setup to continuously monitor potential avalanche slopes in high-alpine terrain, located in the Western Austrian Alps during two consecutive winters (2012/13 & 2013/14). To acquire and analyse the data, an elaborate scanner control and data processing framework was developed and implemented. The results show, that the ATLS setup is able to provide an almost complete series of scans of the target areas every 12h, at a mean point spacing of 0.4-1.1 m and an accuracy of ± 0.05 m (la), plus a distance dependent error of <; 20 ppm. An overview of limitations and further potential of these techniques conclude the paper.

System for on-line 3D measurement of rough natural surfaces

3D reconstruction of highly textured surfaces like those found in roads, as well as unvegetated (rock-like) terrain is of major interest for applications like autonomous navigation, or the 3D modeling of terrain for mapping purposes. We describe a system for automatic modeling of such scenes. It is based on two frame CCD cameras, which are tightly attached to eachother to ensure constant relative orientation. One camera is used for the acquisition of photogrammetrically measure reference points, the other records the surface images. The system is moved from the first position to the next by an operator carrying it. Automatic calibration using the images acquired by the calibration camera permits the computation of exterior orientation parameters of the surface camera. A fast matching method providing dense disparities together with a robust reconstruction algorithm renders an accurate grid of 3D points. We also describe procedures to merge stereo reconstruction results from all images taken, and report on accuracy, computational complexity, and practical experience in a road engineering application.