This paper considers a novel indoor positioning method that is currently under development at the ETH Zurich. The method relies on a digital spatio-semantic interior building model CityGML and a Range Imaging sensor. In contrast to common indoor positioning approaches, the procedure presented here does not require local physical reference infrastructure, such as WLAN hot spots or reference markers.

Topographic measurements are essential for the study of earth surface processes. Three‐dimensional data have been conventionally obtained through terrestrial laser scanning or photogrammetric methods. However, particularly in steep and rough terrain, high‐resolution field measurements remain challenging and often require new creative approaches. In this paper, range imaging is evaluated as an alternative method for obtaining surface data in such complex environments. Range imaging is an emerging time‐of‐flight technology, using phase shift measurements on a multi‐pixel sensor to generate a distance image of a surface. Its suitability for field measurements has yet not been tested. We found ambient light and surface reflectivity to be the main factors affecting error in distance measurements. Low‐reflectivity surfaces and strong illumination contrasts under direct exposure to sunlight lead to noisy distance measurements. However, regardless of lighting conditions, the accuracy of range imaging was markedly improved by averaging multiple images of the same scene. For medium ambient lighting (shade) and a light‐coloured surface the measurement uncertainty was approximately 9 mm. To further test the suitability of range imaging for field applications we measured a reach of a steep mountain stream with a horizontal resolution of approximately 1 cm (in the focal plane of the camera), allowing for the interpolation of a digital elevation model on a 2 cm grid. Comparison with an elevation model obtained from terrestrial laser scanning for the same site revealed that both models show similar degrees of topographic detail. Despite limitations in measurement range and accuracy, particularly at bright ambient lighting, range imaging offers three‐dimensional data in real time and video mode without the need of post‐processing. Therefore, range imaging is a useful complement or alternative to existing methods for high‐resolution measurements in small‐ to medium‐scale field sites. Copyright © 2012 John Wiley & Sons, Ltd.

ABSTRACT:This paper presents the first experience of a close range bird's eye view photogrammetry with range imaging (RIM) sensors for the real time generation of high resolution geo-referenced 3D surface models. The aim of this study was to develop a mobile, versatile and less costly outdoor survey methodology to measure natural surfaces compared to the terrestrial laser scanning (TLS). Two commercial RIM cameras (SR4000 by MESA Imaging AG and a CamCube 2.0 by PMDTechnologies GmbH) were mounted on a lightweight crane and on an unmanned aerial vehicle (UAV). The field experiments revealed various challenges in real time deployment of the two state-of-the-art RIM systems, e.g. processing of the large data volume. Acquisition strategy and data processing and first measurements are presented. The precision of the measured distances is less than 1 cm for good conditions. However, the measurement precision degraded under the test conditions due to direct sunlight, strong illumination contrasts and helicopter vibrations. * Corresponding author. Tel. +41 44 633 30 41

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Commission I, WG I/V KEY WORDS: RIM, UAV, tracking, differential GNSS, mapping, DEM/DTM ABSTRACT:Unmanned Aerial Vehicles (UAVs) are more and more used in civil areas like geomatics. Autonomous navigated platforms have a great flexibility in flying and manoeuvring in complex environments to collect remote sensing data. In contrast to standard technologies such as aerial manned platforms (airplanes and helicopters) UAVs are able to fly closer to the object and in small-scale areas of high-risk situations such as landslides, volcano and earthquake areas and floodplains. Thus, UAVs are sometimes the only practical alternative in areas where access is difficult and where no manned aircraft is available or even no flight permission is given. Furthermore, compared to terrestrial platforms, UAVs are not limited to specific view directions and could overcome occlusions from trees, houses and terrain structures. Equipped with image sensors and/or laser scanners they are able to provide elevation models, rectified images, textured 3D-models and maps. In this paper we will describe a UAV platform, which can carry a range imaging (RIM) camera including power supply and data storage for the detailed mapping and monitoring of complex structures, such as alpine riverbed areas. The UAV platform NEO from Swiss UAV was equipped with the RIM camera CamCube 2.0 by PMD Technologies GmbH to capture the surface structures. Its navigation system includes an autopilot. To validate the UAV-trajectory a 360° prism was installed and tracked by a total station. Within the paper a workflow for the processing of UAV-RIM data is proposed, which is based on the processing of differential GNSS data in combination with the acquired range images. Subsequently, the obtained results for the trajectory are compared and verified with a track of a UAV (Falcon 8, Ascending Technologies) carried out with a total station simultaneously to the GNSS data acquisition. The results showed that the UAV's position using differential GNSS could be determined in the centimetre to the decimetre level. The RIM data indicated a high noise level in the measured distance image, due to the vibrations caused by the flight system. Multi-image processing reduced the noise level of the distance image. The produced elevation models from a test area show the high potential of the proposed method for complex structures such as riverbeds.