Wyniki wyszukiwania - BazTech

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Motion estimation by integrated low cost system (vision and MEMS) for positioning of a scooter "Vespa"

Guarnieri A., Milan N., Pirotti F., Vettore A.

Archiwum Fotogrametrii, Kartografii i Teledetekcji

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2011

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Vol. 22

147--158

EN

In the automotive sector, especially in these last decade, a growing number of investigations have taken into account electronic systems to check and correct the behaviour of drivers, increasing road safety. The possibility to identify with high accuracy the vehicle position in a mapping reference frame for driving directions and best-route analysis is also another topic which attracts lot of interest from the research and development sector. To reach the objective of accurate vehicle positioning and integrate response events, it is necessary to estimate time by time the position, orientation and velocity of the system. To this aim low cost GPS and MEMS (sensors can be used. In comparison to a four wheel vehicle, the dynamics of a two wheel vehicle (e.g. a scooter) feature a higher level of complexity. Indeed more degrees of freedom must be taken into account to describe the motion of the latter. For example a scooter can twist sideways, thus generating a roll angle. A slight pitch angle has to be considered as well, since wheel suspensions have a higher degree of motion with respect to four wheel vehicles. In this paper we present a method for the accurate reconstruction of the trajectory of a motorcycle (“Vespa” scooter), which can be used as alternative to the “classical” approach based on the integration of GPS and INS sensors. Position and orientation of the scooter are derived from MEMS data and images acquired by on-board digital camera. A Bayesian filter provides the means for integrating the data from MEMS-based orientation sensor and the GPS receiver.

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Dynamic vision for motion determination of Mobile Mapping System

Crocetto N., Guarnieri A., Vettore A.

Reports on Geodesy

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2002

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z. 1/61

261-264

EN

One of the main components of a Mobile Mapping System is represented by the Intertial Navigation Unit (INS) which along with an on-board GPS receiver allows the retreval of the van trajectory. Drifts are the main drawback of INS, affecting the overall positioning precision of the van. In order to improve its performance two solutions have been approached: 1) processing and adjustment of GPS and INS errors by Kalman filtering 2) employing of expensive INS, which leads, unfortunately , to considerable increase of the final cost of the whole system. An MMS is also tipically provided with at least two CCD cameras (color or B/N). by which the possitioning information of interesting land features can be acquired. This operation relies upon algorithms, such as camera calibration, space resection, image processing, developed for Digital Photogrammetry and Computer Vision. Given this background, in this work we propose to investigate the feasability of a dynamic model to retrieve the van motion via monocular vision, avoiding the use of INS.

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Geovision: a digital photogrammetric software for road survey

Bartolozzo A., Guarnieri A., Vettore A.

Reports on Geodesy

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1999

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z. 3/44

155-164

EN

In this work an alternative method, respect today's tipical road survey, is presented. Tipically, a road survey is carried out by a team composed by three operators at least, that moves with a wehicle on which an odometer is mounted on the rear in order to measure the effective travelled road. Given this procedure, such a survey requires, as a rule, a lot of time, therefore it can result very laborious and expensive regarding the employement of economic and human resources. Possible solutions to these problems could be represented by integration of Computer Vision technology with modem satellite positioning system, as GPS. Also in agreement with this idea, GeoVision, a digital photogrammetric software for road survey, has been developed at the University of Padua (Itały). The system consists of two digital cameras, Sony XC75CE, mounted on the front of a vehicle, recording in continous way the surveyed environment and a GPS receiver that provides post-processed differential positions. From a pair of correspondent digital images, the 3D posrtion of a feature can be determined in a global reference system (namely WGS-84), by integration of photogrammetric triangulation techniques and computer vision algoritms. In following sections the tools regarding digital image processing subsystem of GeoVision will be described in detail.