Trajectography of an uncalibrated stereo rig in urban environments

Simond, Nicolas; Rives, Patrick

doi:10.1109/iros.2004.1389939

Cited by 7 publications

(3 citation statements)

References 12 publications

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“…Since the initial results of [35], great progress has been made in the related problem of visual odometry [36]- [39]. Visual odometry systems have the important advantage of constant time execution.…”

Section: Introduction: State-of-the Art In Visual Slammentioning

confidence: 99%

Large-Scale 6-DOF SLAM With Stereo-in-Hand

et al. 2008

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Section: Introduction: State-of-the Art In Visual Slammentioning

confidence: 99%

Large-Scale 6-DOF SLAM With Stereo-in-Hand

et al. 2008

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“…This would work well in a room for example, but it is not suitable if the robot needs to travel for hundreds of meters. It is also possible to compute ego motion by using only visual data as done by Nistér et al (2004) or, in the specific case of urban environment (Simond and Rives, 2004). In this case, maintaining a large map is not required but the localization accuracy decreases as the distance traveled increases.…”

Section: Related Workmentioning

confidence: 99%

Monocular Vision for Mobile Robot Localization and Autonomous Navigation

Royer

Lhuillier

Dhome

et al. 2007

Int J Comput Vision

292

185

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International audienceThis paper presents a new real-time localization system for a mobile robot. We show that autonomous navigation is possible in outdoor situation with the use of a single camera and natural landmarks. To do that, we use a three step approach. In a learning step, the robot is manually guided on a path and a video sequence is recorded with a front looking camera. Then a structure from motion algorithm is used to build a 3D map from this learning sequence. Finally in the navigation step, the robot uses this map to compute its localization in real-time and it follows the learning path or a slightly different path if desired. The vision algorithms used for map building and localization are first detailed. Then a large part of the paper is dedicated to the experimental evaluation of the accuracy and robustness of our algorithms based on experimental data collected during two years in various environments

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“…A classical approach for cars is to obtain totally [15] or partially [14] the camera displacement by observing the homography described by the road plane. The a priori knowledge of camera/ground distance is then used to constrain the scale factor.…”

Section: Related Workmentioning

confidence: 99%

Real-time vehicle global localisation with a single camera in dense urban areas: Exploitation of coarse 3D city models

Lothe

Bourgeois

Royer

et al. 2010

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition

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In this system paper, we propose a real-time car localisation process in dense urban areas by using a single perspective camera and a priori on the environment. To tackle this problem, it is necessary to solve two well-known monocular SLAM limitations: scale factor drift and error accumulation. The proposed idea is to combine a monocular SLAM process based on bundle adjustment with simple knowledge, i.e. the position and orientation of the camera with regard to the road and a coarse 3D model of the environment, as those provided by GIS database. First, we show that, thanks to specific SLAM-based constraints, the road homography can be expressed only with respect to the scale factor parameter. This allows the scale factor to be robustly and frequently estimated. Then, we propose to use the global information brought by 3D city models in order to correct the monocular SLAM error accumulation. Even with coarse 3D models, turnings give enough geometrical constraints to allow fitting the reconstructed 3D point cloud with the 3D model. Experiments on large-scale sequences (several kilometres) show that the entire process permits the real-time localisation of a car in city centre, even in real traffic condition.

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Trajectography of an uncalibrated stereo rig in urban environments

Cited by 7 publications

References 12 publications

Large-Scale 6-DOF SLAM With Stereo-in-Hand

Large-Scale 6-DOF SLAM With Stereo-in-Hand

Monocular Vision for Mobile Robot Localization and Autonomous Navigation

Real-time vehicle global localisation with a single camera in dense urban areas: Exploitation of coarse 3D city models

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