Odometry and Low-Cost Sensor Fusion in Tmm Dataset

The aim of this study is to identify the most powerful motion model and filtering technique to represent an urban terrestrial mobile mapping (TMM) survey and ultimately to obtain the best representation of the car trajectory. The authors want to test how far a motion model and a more or less refined filtering technique could bring benefits in the determination of the car trajectory. To achieve the necessary data for the application of the motion models and the filtering techniques described in the article, the authors realized a TMM survey in the urban centre of Turin by equipping a vehicle with various instruments: a low-cost action-cam also able to record the GPS trace of the vehicle even in the presence of obstructions, an inertial measurement system and an odometer. The results of analysis show in the article indicate that the Unscented Kalman Filter (UKF) technique provides good results in the determination of the vehicle trajectory, especially if the motion model considers more states (such as the positions, the tangential velocity, the angular velocity, the heading, the acceleration). The authors also compared the results obtained with a motion model characterized by four, five and six states. A natural corollary to this work would be the introduction to the UKF of the photogrammetric information obtained by the same camera placed on board the vehicle. These data would permit to establish how photogrammetric measurements can improve the quality of TMM solutions, especially in the absence of GPS signals (like urban canyons)

ON OUTLIER DETECTION IN A PHOTOGRAMMETRIC MOBILE MAPPING DATASET

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

ODOMETRY AND LOW-COST SENSOR FUSION IN TMM DATASET

The aim of this study is to identify the most powerful motion model and filtering technique to represent an urban terrestrial mobile mapping (TMM) survey and ultimately to obtain the best representation of the car trajectory. The authors want to test how far a motion model and a more or less refined filtering technique could bring benefits in the determination of the car trajectory. To achieve the necessary data for the application of the motion models and the filtering techniques described in the article, the authors realized a TMM survey in the urban centre of Turin by equipping a vehicle with various instruments: a low-cost action-cam also able to record the GPS trace of the vehicle even in the presence of obstructions, an inertial measurement system and an odometer. The results of analysis show in the article indicate that the Unscented Kalman Filter (UKF) technique provides good results in the determination of the vehicle trajectory, especially if the motion model considers more states (such as the positions, the tangential velocity, the angular velocity, the heading, the acceleration). The authors also compared the results obtained with a motion model characterized by four, five and six states. A natural corollary to this work would be the introduction to the UKF of the photogrammetric information obtained by the same camera placed on board the vehicle. These data would permit to establish how photogrammetric measurements can improve the quality of TMM solutions, especially in the absence of GPS signals (like urban canyons)

L'accuratezza dei DTM per analisi idrologiche

Eventi di dissesto idrogeologico sono sempre più frequenti, soprattutto a causa di interventi antropici sregolati, che avvengono senza una pianificazione attenta del territorio e senza un’analisi dei rischi adeguata. Per poter compiere tali operazioni è necessario basarsi su strumenti cartografici che permettono di rappresentare il territorio stesso: tra i principali strumenti in questione vi sono i DTM (Digital Terrain Model), i quali rappresentano morfologicamente l’elevazione del terreno e permettono quindi svariate analisi idrologiche. Nel presente lavoro verrà mostrato come la qualità dei DTM a disposizione e di conseguenza le informazioni idrologiche ad essi collegati, non siano legate soltanto al passo della maglia e alla precisione altimetrica dichiarata, ma anche alle verifiche effettuate durante la sua costruzione per migliorarne la qualità ed eliminare errori sistematici o grossolani localizzati e nascosti nell’insieme di queste grandi moli di dati da gestire

Real-time monitoring for fast deformations using GNSS low-cost receivers

Landslides are one of the major geo-hazards which have constantly affected Italy especially over the last few years. In fact 82% of the Italian territory is affected by this phenomenon which destroys the environment and often causes deaths: therefore it is necessary to monitor these effects in order to detect and prevent these risks. Nowadays, most of this type of monitoring is carried out by using traditional topographic instruments (e.g. total stations) or satellite techniques such as global navigation satellite system (GNSS) receivers. The level of accuracy obtainable with these instruments is sub-centimetrical in post-processing and centimetrical in real-time; however, the costs are very high (many thousands of euros). The rapid diffusion of GNSS networks has led to an increase of using mass-market receivers for real-time positioning. In this paper, the performances of GNSS mass-market receiver are reported with the aim of verifying if this type of sensor can be used for real-time landslide monitoring: for this purpose a special slide was used for simulating a landslide, since it enabled us to give manual displacements thanks to a micrometre screw. These experiments were also carried out by considering a specific statistical test (a modified Chow test) which enabled us to understand if there were any displacements from a statistical point of view in real time. The tests, the algorithm and results are reported in this paper

ON OUTLIER DETECTION IN A PHOTOGRAMMETRIC MOBILE MAPPING DATASET

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

Il posizionamento NRTK in alta quota: applicazioni e risultati nell'ambito del progetto Helidem

Il presente lavoro si colloca nel progetto INTERREG Italia-Svizzera 2007-2013 HELIDEM. In tale ambito era prevista ed è stata istituita una rete di stazioni permanenti a copertura delle aree alpine di Piemonte, Lombardia e parte della Svizzera. Tale rete costituisce un prototipo, seppur limitato a una piccola area, di servizio di posizionamento transnazionale ottenuto mediante unificazione di reti regionali già installate: inoltre, nell'ambito del progetto, fornirà il sistema di riferimento per rilievi (in tempo reale e post-elaborati) finalizzati all'unificazione dei Modelli Digitali dei Terreno e del modello delle altezze (geoide) per le aree di progetto. Nel presente lavoro viene descritta la rete e le modalità con cui è stata inquadrata nel sistema di riferimento ETRF2000. Vengono inoltre discussi i primi test di posizionamento cinematico, sia in tempo reale sia post-elaborato, appoggiato alla rete. Particolarmente interessanti sono i confronti fra risultati in bassa e alta quota, che permettono considerazioni non intuitiv

On outlier detection in a photogrammetric mobile mapping dataset

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

Implementazione della rete GNSS di riferimento

E’ stata istituita una rete di stazioni permanenti GNSS a copertura delle aree alpine del Piemonte, della Lombardia e di parte della Svizzera. Tale rete costituisce un prototipo di un servizio di posizionamento transnazionale ottenuto mediante l’unificazione di reti regionali già installate: inoltre, nell’ambito del presente progetto, ha lo scopo di materializzare il sistema di riferimento per i rilievi in tempo reale e post-processati finalizzati all’unione dei DTM e del modello di altezze. Il presente capitolo descrive il prototipo di rete e le modalità con cui è stata inquadrata nel sistema di riferimento ETRF2000. Vengono inoltre descritti i primi test di posizionamento cinematico, sia in tempo reale sia post-elaborato, appoggiato alla rete