Terrestrial Mobile Research Articles

Special Issue: Smart Satellite Systems

Special Issue: Smart Satellite Systems

A FAST AND ROBUST ALGORITHM FOR ROAD EDGES EXTRACTION FROM LIDAR DATA

Fast mapping of roads plays an important role in many geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance. How to extract various road edges fast and robustly is a challenging task. In this paper, we present a fast and robust algorithm for the automatic road edges extraction from terrestrial mobile LiDAR data. The algorithm is based on a key observation: most roads around edges have difference in elevation and road edges with pavement are seen in two different planes. In our algorithm, we firstly extract a rough plane based on RANSAC algorithm, and then multiple refined planes which only contains pavement are extracted from the rough plane. The road edges are extracted based on these refined planes. In practice, there is a serious problem that the rough and refined planes usually extracted badly due to rough roads and different density of point cloud. To eliminate the influence of rough roads, the technology which is similar with the difference of DSM (digital surface model) and DTM (digital terrain model) is used, and we also propose a method which adjust the point clouds to a similar density to eliminate the influence of different density. Experiments show the validities of the proposed method with multiple datasets (e.g. urban road, highway, and some rural road). We use the same parameters through the experiments and our algorithm can achieve real-time processing speeds.

A FAST AND ROBUST ALGORITHM FOR ROAD EDGES EXTRACTION FROM LIDAR DATA

Abstract. Fast mapping of roads plays an important role in many geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance. How to extract various road edges fast and robustly is a challenging task. In this paper, we present a fast and robust algorithm for the automatic road edges extraction from terrestrial mobile LiDAR data. The algorithm is based on a key observation: most roads around edges have difference in elevation and road edges with pavement are seen in two different planes. In our algorithm, we firstly extract a rough plane based on RANSAC algorithm, and then multiple refined planes which only contains pavement are extracted from the rough plane. The road edges are extracted based on these refined planes. In practice, there is a serious problem that the rough and refined planes usually extracted badly due to rough roads and different density of point cloud. To eliminate the influence of rough roads, the technology which is similar with the difference of DSM (digital surface model) and DTM (digital terrain model) is used, and we also propose a method which adjust the point clouds to a similar density to eliminate the influence of different density. Experiments show the validities of the proposed method with multiple datasets (e.g. urban road, highway, and some rural road). We use the same parameters through the experiments and our algorithm can achieve real-time processing speeds.

Boresight and Lever Arm Calibration of a Mobile Terrestrial LiDAR System

Unlike Mobile Airborne LiDAR (MAL), it has become common for Mobile Terrestrial LiDAR (MTL) sys tems to consist of two or more LiDAR sensors. It is a challenging task for a user to simultaneously verify and calibrate their lever arms and boresight angles with respect to the IMU using the kinematic data. This paper presents a novel method for determination of MTL calibration parameters using the vector geometry created by a stereo pair of MTL sensors. Through the use of the stereo information provided by a pair of MTL sensors working in tandem, system parameters such as lever arm and boresight angles can be deter mined for both sen sors based on a single pass of a calibration object or scene. In this way, any data collected by a multi-sensor MTL can potentially be used to calibrate the system. Unlike many other calibration methods for calibrating MTL and MAL systems, the proposed method enables the simultaneous calibration of all lever arm and bore sight parameters for all of the LiDAR sensors integrated into the MTL system. Many MTL systems do not make it easy for end users to measure the lever arms, usually forcing users to fall back on mechanical drawings to determine the lever arms. The calibration method has been realized using test data acquired by two inde pend ent Lynx Mobile Mapper systems on 1) a single pass of a typical 400-m-long urban street scene and 2) a single pass around a calibration building. Each experiment succeeded at producing arc - second accurate boresight and sub-centimetre accurate lever arm parameters. Several scenarios were run. It was found that this accuracy level could be practically maintained with a control field consisting of five to seven control points dis tributed on horizontal and vertical surfaces.

Mapping Vineyard Leaf Area Using Mobile Terrestrial Laser Scanners: Should Rows be Scanned On-the-Go or Discontinuously Sampled?

The leaf area index (LAI) is defined as the one-side leaf area per unit ground area, and is probably the most widely used index to characterize grapevine vigor. However, LAI varies spatially within vineyard plots. Mapping and quantifying this variability is very important for improving management decisions and agricultural practices. In this study, a mobile terrestrial laser scanner (MTLS) was used to map the LAI of a vineyard, and then to examine how different scanning methods (on-the-go or discontinuous systematic sampling) may affect the reliability of the resulting raster maps. The use of the MTLS allows calculating the enveloping vegetative area of the canopy, which is the sum of the leaf wall areas for both sides of the row (excluding gaps) and the projected upper area. Obtaining the enveloping areas requires scanning from both sides one meter length section along the row at each systematic sampling point. By converting the enveloping areas into LAI values, a raster map of the latter can be obtained by spatial interpolation (kriging). However, the user can opt for scanning on-the-go in a continuous way and compute 1-m LAI values along the rows, or instead, perform the scanning at discontinuous systematic sampling within the plot. An analysis of correlation between maps indicated that MTLS can be used discontinuously in specific sampling sections separated by up to 15 m along the rows. This capability significantly reduces the amount of data to be acquired at field level, the data storage capacity and the processing power of computers.

Construction and evaluation of interactive services in TVDi environments.

Context : In order to expand the range of virtual education opportunities, it’s important to consider two technological aspects: the great potential of TV penetration and the Web 2.0 services boom in social networks and Internet communities, spaces in which users share and generate knowledge around a topic. So, it’s necessary to define how to implement and deploy these interactive services in television environments, given the particular characteristics of this scenario. Method : For the purpose of guiding the building process of interactive services, in this paper we propose a scheme of service consumption in scenarios of interactive digital television (iDTV), which has been adapted from the REST-JSON (Representational State Transfer – Javascript Object Notation) architectural style. Results : As a result of the use of the proposed scheme, we implemented the message board, chat and e-mail services, in the television scenarios of digital terrestrial television (DTT) and Mobile TV of the ST-CAV project (T-Learning services for the support of virtual academic communities). Likewise, another result obtained in the present paper, was the evaluation of the implemented services through network traffic and memory consumption tests. Conclusions : According to processing and response times obtained in the evaluation of implemented interactive services, the presented scheme can be considered as a viable alternative for the design and building of services in iDTV scenarios, allowing convergence with Internet applications (Web 2.0).

Empirical Geometry-Based Random-Cluster Model for High-Speed-Train Channels in UMTS Networks

In this paper, a recently conducted measurement campaign for high-speed-train (HST) channels is introduced, where the downlink signals of an in-service Universal Mobile Terrestrial System (UMTS) deployed along an HST railway between Beijing and Shanghai were acquired. The channel impulse responses (CIRs) are extracted from the data received in the common pilot channels (CPICHs). Within 1318 km, 144 base stations (BSs) were detected. Multipath components (MPCs) estimated from the CIRs are clustered and associated across the time slots. The results show that, limited by the sounding bandwidth of 3.84 MHz, most of the channels contain a single line-of-sight (LoS) cluster, and the rest consists of several LoS clusters due to distributed antennas, leaking cable, or neighboring BSs sharing the same CPICH. A new geometry-based random-cluster model is established for the clusters' behavior in delay and Doppler domains. Different from conventional models, the time-evolving behaviors of clusters are characterized by random geometrical parameters, i.e., the relative position of BS to railway, and the train speed. The distributions of these parameters, and the per-cluster path loss, shadowing, delay, and Doppler spreads, are extracted from the measurement data.

SIMPLE APPROACHES TO IMPROVE THE AUTOMATIC INVENTORY OF ZEBRA CROSSING FROM MLS DATA

Abstract. The city management is increasingly supported by information technologies, leading to paradigms such as smart cities, where decision-makers, companies and citizens are continuously interconnected. 3D modelling turns of great relevance when the city has to be managed making use of geospatial databases or Geographic Information Systems. On the other hand, laser scanning technology has experienced a significant growth in the last years, and particularly, terrestrial mobile laser scanning platforms are being more and more used with inventory purposes in both cities and road environments. Consequently, large datasets are available to produce the geometric basis for the city model; however, this data is not directly exploitable by management systems constraining the implementation of the technology for such applications. This paper presents a new algorithm for the automatic detection of zebra crossing. The algorithm is divided in three main steps: road segmentation (based on a PCA analysis of the points contained in each cycle of collected by a mobile laser system), rasterization (conversion of the point cloud to a raster image coloured as a function of intensity data), and zebra crossing detection (using the Hough Transform and logical constrains for line classification). After evaluating different datasets collected in three cities located in Northwest Spain (comprising 25 strips with 30 visible zebra crossings) a completeness of 83% was achieved.

MULTI-PASS APPROACH FOR MOBILE TERRESTRIAL LASER SCANNING

Abstract. Mobile Terrestrial Laser Scanning (MTLS) has been utilised for an increasing number of corridor surveys. Current MTLS surveys require that many targets be placed along the corridor to monitor the MTLS trajectory’s accuracy. These targets enable surveyors to directly evaluate the magnitude of GNSS errors at regular intervals and can also be used to adjust the trajectory to the survey control. However, this “Multi-Target” approach (MTA) is an onerous task that can significantly reduce efficiency. It also is inconvenient to the travelling public, as lanes are often blocked and traffic slowed to permit surveyors to work safely along the road corridor. This paper introduces a “Multi-Pass” approach (MPA), which minimises the number of targets required for monitoring the GNSS-controlled trajectory while still maintaining strict engineering accuracies. MPA uses the power of multiple, independent MTLS passes with different GNSS constellations to generate a “Control Polyline” from the point cloud for the corridor. The Control Polyline can be considered as a statistically valid survey measurement and be incorporated in a network adjustment to strengthen a control network by identifying outliers. Results from a test survey at the MTLS course maintained by the Oregon Department of Transportation illustrate the effectiveness of this approach.

Automatic reconstruction of road surface features by using terrestrial mobile lidar

Abstract As urban roads expand over time, road surface features become more complicated and critical to driving safety. Constructing a database of road surface features through an automatic process is particularly crucial when these features are applied to the fields of facility maintenance, autonomous vehicle assistance, 3D cyber city construction, and navigation-information renewal. This paper proposes a fully automatic approach for reconstructing road surface features based on the terrestrial mobile light detection and ranging (lidar) technique. Analysis steps were developed and an experiment was performed using a real lidar data set. The results indicated that the proposed road surface reconstruction method is feasible and that the classification indices, correctness and completeness, were both higher than 90%. Finally, the uncertainty associated with each analysis stage was explicitly assessed through an error budget analysis. This can provide a guideline for practical applications and further system optimization.

Empirical Radiometric Normalization of Road Points from Terrestrial Mobile Lidar System

Lidar data provide both geometric and radiometric information. Radiometric information is influenced by sensor and target factors and should be calibrated to obtain consistent energy responses. The radiometric correction of airborne lidar system (ALS) converts the amplitude into a backscatter cross-section with physical meaning value by applying a model-driven approach. The radiometric correction of terrestrial mobile lidar system (MLS) is a challenging task because it does not completely follow the inverse square range function at near-range. This study proposed a radiometric normalization workflow for MLS using a data-driven approach. The scope of this study is to normalize amplitude of road points for road surface classification, assuming that road points from different scanners or strips should have similar responses in overlapped areas. The normalization parameters for range effect were obtained from crossroads. The experiment showed that the amplitude difference between scanners and strips decreased after radiometric normalization and improved the accuracy of road surface classification.

ON OUTLIER DETECTION IN A PHOTOGRAMMETRIC MOBILE MAPPING DATASET

Abstract. Various types of technology are used for Terrestrial Mobile Mapping (TMM) such as IMU, cameras, odometers, laser scanner etc., which are integrated in order to determine the attitude and the position of the vehicle in use, especially in the absence of GNSS signal i.e. in an urban canyon. The aim of this study is to use only photogrammetric measurements obtained with a low cost camera (with a reduced focal length and small frames) located on the vehicle, in order to improve the quality of TMM solution in the absence of a GNSS signal. It is essential to have good quality frames in order to solve this problem. In fact it is generally quite easy to extract a large number of common points between the frames (the so-called ‘tie points’), but this does not necessarily imply the goodness of the matching quality, which might be uncorrected due to the presence of obstacles that may occlude the camera sight. The Authors used two different methods for solving the problem of the presence of outliers: RANSAC and the Forward Search. In this article the Authors show the results obtainable with good quality frames (frames without occlusions) and under difficult conditions that simulate better reality.

A Three-Component Model Based on Macropropagation Phenomena Approach for Complex Building Scattering

Multipaths represent a common predominant and uncontrolled component on channel impairments for all terrestrial and Land Mobile Satellite systems. Without restrictions w.r.t mobile terrestrial applications, the addressed multipath problematic in this paper is focused on Land Mobile Satellite applications where delayed signal replicas are highly impacting performances on communication systems while they induce strong positioning errors for navigation systems. The actual trend in propagation channel modelling is to improve the multipath characterisation and representation by using semideterministic and hybrid physical-statistical models into channel simulators instead of narrow-band empirical approaches. In this context, this paper presents a new simplified model, called 3CM (3-Component Model) to reproduce building scattering in an efficient way which strongly improves computation performances. This model is based on asymptotic methods, namely, PO (Physical Optics) which allows the 3CM to be frequency scalable, polarimetric, and dielectric materials oriented. Note that the proposed model and the retained approach can be integrated into more complex tools such as existing ray tracers. However, this issue is not discussed in this paper.

A Time Variant Outdoor-to-Indoor Channel Model for Mobile Radio Based Navigation Applications

Time based positioning with terrestrial mobile radio signals has gained remarkable attention. To develop and validate positioning algorithms under realistic conditions, an accurate knowledge of the propagation channel is significant. However, there is still a lack of outdoor-to-indoor channel models suitable for positioning applications. To be applicable for positioning, the channel model has to fulfill three requirements that have not been accurately considered so far: the non-line-of-sight bias (affecting ranging accuracy), nondiscrete valued channel parameters (affecting algorithm performance), and the evolution of individual multipath components (MPCs) with time (affecting tracking performance). In this paper, an outdoor-to-indoor channel model is proposed based on an extension of the geometry-based stochastic modeling approach to fulfill the requirements. We consider MPCs occurring due to reflection, scattering, and combinations of both. In the model, three different types of MPCs are modeled separately according to their characteristics. Each MPC is represented by a fixed scatterer, which has a fixed position while the receiver antenna is moving. The parameters of the outdoor-to-indoor channel model are extracted from two channel measurement campaigns. The proposed outdoor-to-indoor channel model is capable of accurately simulating the time variant channel. A comparison of the channel model with the channel measurement data is performed by comparing statistics.

Surface-Based Registration of Airborne and Terrestrial Mobile LiDAR Point Clouds

Light Detection and Ranging (LiDAR) is an active sensor that can effectively acquire a large number of three-dimensional (3-D) points. LiDAR systems can be equipped on different platforms for different applications, but to integrate the data, point cloud registration is needed to improve geometric consistency. The registration of airborne and terrestrial mobile LiDAR is a challenging task because the point densities and scanning directions differ. We proposed a scheme for the registration of airborne and terrestrial mobile LiDAR using the least squares 3-D surface registration technique to minimize the surfaces between two datasets. To analyze the effect of point density in registration, the simulation data simulated different conditions and estimated the theoretical errors. The test data were the point clouds of the airborne LiDAR system (ALS) and the mobile LiDAR system (MLS), which were acquired by Optech ALTM 3070 and Lynx, respectively. The resulting simulation analysis indicated that the accuracy of registration improved as the density increased. For the test dataset, the registration error of mobile LiDAR between different trajectories improved from 40 cm to 4 cm, and the registration error between ALS and MLS improved from 84 cm to 4 cm. These results indicate that the proposed methods can obtain 5 cm accuracy between ALS and MLS.

Object Detection in Terrestrial Laser Scanning Point Clouds Based on Hough Forest

This letter presents a novel rotation-invariant method for object detection from terrestrial 3-D laser scanning point clouds acquired in complex urban environments. We utilize the Implicit Shape Model to describe object categories, and extend the Hough Forest framework for object detection in 3-D point clouds. A 3-D local patch is described by structure and reflectance features and then mapped to the probabilistic vote about the possible location of the object center. Objects are detected at the peak points in the 3-D Hough voting space. To deal with the arbitrary azimuths of objects in real world, circular voting strategy is introduced by rotating the offset vector. To deal with the interference of adjacent objects, distance weighted voting is proposed. Large-scale real-world point cloud data collected by terrestrial mobile laser scanning systems are used to evaluate the performance. Experimental results demonstrate that the proposed method outperforms the state-of-the-art 3-D object detection methods.

Error Analysis of a Mobile Terrestrial LiDAR System

The understanding of the effects of error on Mobile Terrestrial LiDAR (MTL) point clouds has not increased with their popularity. In this study, comprehensive error analyses based on error propagation theory and global sensitivity study were carried out to quantitatively describe the effects of various error sources in a MTL system on the point cloud. Two scenarios were envisioned; the first using the uncertainties for measurement and calibration variables that are normally expected for MTL systems as they exist today, and the second using an ideal situation where measurement and calibration values have been well adjusted. It was found that the highest proportion of error in the point cloud can be attributed to the boresight and lever arm parameters for MTL systems calibrated using non-rigours methods. In particular, under a loosely controlled error condition, the LiDAR to INS Z lever arm and the LiDAR to INS roll angle contributed more error in the output point cloud than any other parameter, including the INS position. Under tightly controlled error conditions, the INS position became the dominant source of error in the point cloud. In addition, conditional variance analysis has shown that the majority of the error in a point cloud can be attributed to the individual variables. Errors caused by the interactions between the diverse variables are minimal and can be regarded as insignificant.

Monitoring marginal erosion in hydroelectric reservoirs with terrestrial mobile laser scanner

Abstract. Marginal erosions in reservoirs of hydroelectric plants have caused economic and environmental problems concerning hydroelectric power generation, reduction of productive areas and devaluing land parcels. The real extension and dynamics of these erosion processes are not well known for Brazilian reservoirs. To objectively assess these problems Unesp (Univ Estadual Paulista) and Duke Energy are developing a joint project which aims at the monitoring the progression of some erosive processes and understanding the causes and the dynamics of this phenomenon. Mobile LASER scanning was considered the most suitable alternative for the challenges established in the project requirements. A MDL DynaScan Mobile LASER M150 scanner was selected which uses RTK for real time positioning integrated to an IMU, enabling instantaneous generation of georeferenced point clouds. Two different reservoirs were choose for monitoring: Chavantes (storage plant) and Rosana (run-of-river plant), both in the Paranapanema River, border of São Paulo and Paraná States, Brazil. The monitoring areas are scanned quarterly and analysed with base on the point cloud, meshes, contours and cross sections. Cross sections are used to visualize and compute the rate and the dynamics of erosion. Some examples and quantitative results are presented along with an analysis of the proposed technique. Some recommendations to improve the field work and latter data processing are also introduced.

The requirements, challenges, and technologies for 5G of terrestrial mobile telecommunication

In this article, we summarize the 5G mobile communication requirements and challenges. First, essential requirements for 5G are pointed out, including higher traffic volume, indoor or hotspot traffic, and spectrum, energy, and cost efficiency. Along with these changes of requirements, we present a potential step change for the evolution toward 5G, which shows that macro-local coexisting and coordinating paths will replace one macro-dominated path as in 4G and before. We hereafter discuss emerging technologies for 5G within international mobile telecommunications. Challenges and directions in hardware, including integrated circuits and passive components, are also discussed. Finally, a whole picture for the evolution to 5G is predicted and presented.

Planetary robotics exploration activities at DLR

Intelligent mobility, agile manipulability, and increased autonomy are key technologies to guarantee for long-range and efficient surface exploration on Earth’s Moon and on planets. In order to increase the scientific output of a rover mission it is very necessary to explore much larger surface areas reliably in much less time. This is the main driver for a robotics institute to combine mechatronics functionalities to develop an intelligent mobile vehicle with an appropriate number of wheels, and having specific kinematics and locomotion suspension depending on the operational terrain of the rover to operate. Moreover, a shift from a traditional bogie and wheel design to more agile wheel-legged combined systems seems to be beneficial to reach the goals. DLR’s Robotics and Mechatronics Center has a long tradition in developing advanced components in the field of light-weight motion actuation, intelligent and soft manipulation and skilled hands and tools, perception and cognition, and in increasing the autonomy of any kind of mechatronic systems. The whole design is supported and is based upon detailed modelling, optimization, and simulation tasks. We have developed efficient software tools to simulate the rover driveability performance on various terrain characteristics such as soft sandy and hard rocky terrains as well as on slopes, where wheel and grouser geometry plays a dominant role. Moreover, first rover designs by best engineering intuitions has to be supported by means of optimization tools from the very beginning. By this, we optimize structural, geometric, and inertia parameters and we compare various kinematics suspension concepts, while making use of realistic cost functions like mass and consumed energy minimization, static stability, and more. For self-localization and safe navigation through unknown terrain we make use of fast 3D stereo algorithms that were successfully used in terrestrial mobile systems. The advanced rover design approach is applicable for lunar as well as Martian surface exploration purposes.