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This doctoral thesis deals with an open subproblem of robot navigation, namely simultaneous localization and mapping (SLAM) in three-dimensional space. The goal is to develop a system which is capable of localizing a mobile robot in a reliable way and at t ...
In this paper we derive theoretical results for the problem of on-line sensor calibration for a mobile robot. We consider the case of the odometry sensor. A first series of results regards the problem of understanding if a given system (consisting of a rob ...
This paper presents a method for probabilistic plane fitting and an application to robotic 3D mapping. The plane is fitted in an orthogonal least-square sense and the output complies with the conventions of the Symmetries and Perturbation model (SPmodel). ...
This paper presents the extension and experimental validation of the widely used EKF1-based SLAM2 algorithm to 3D space. It uses planar features extracted probabilistically from dense three-dimensional point clouds generated by a rotating 2D laser scanner. ...
This paper presents an improved feature-based 3D SLAM approach for a mobile robot equipped with a rotating laser scanner. The features are represented within the SPmodel, with associated planar segment information based on decimated triangle sets. An Exten ...
This paper describes an algorithm for generating compact feature-based 3D models of indoor environments with a mobile robot. The emphasis lies on the high performance of the algorithm, its possible incremental use, as well as its wide applicability to a va ...