This paper introduces a new approach to SLAM which combines an Information Filter and a non linear optimizer. The basic idea of the suggested technique is to use the Information Filter when the system non linearities are negligible, and to switch to the use of the non linear optimizer when the non linearities are not negligible. Extensive simulations are provided in order to evaluate the performance of the proposed approach. In particular, a comparison with the Exactly Sparse Delayed-state Filers (ESDF) technique is carried out
Extended Kalman filter (EKF) is often employed in determining the position of mobile robot and landm...
The computational bottleneck in all informationbased algorithms for SLAM is the recovery of the stat...
This paper presents an experimentally validated alternative to the classical extended Kalman filter ...
International audienceThis paper introduces a new approach to SLAM which combines an Information Fil...
Abstract: A SLAM algorithm inspired by biological principles has been recently proposed and shown to...
This paper proposes a real-time nonlinear filtering approach for the SLAM problem, termed as compres...
Recently a SLAM algorithm based on biological principles (RatSLAM) has been proposed. It was proven ...
This paper proposes an innovative simultaneous localization and mapping (SLAM) algorithm which combi...
Designing filters exploiting the sparseness of the information matrix for efficiently solving the si...
The process of simultaneously building the map and locating a vehicle is known as Simultaneous Local...
is the development of algorithms which scale with the size of the environment. A few promising metho...
This dissertation describes the development of a method for simultaneous localization and mapping (S...
In this paper we describe the Combined Filter, a judicious combination of Extended Kalman (EKF) and ...
This electronic version was submitted by the student author. The certified thesis is available in th...
The lack of the latest measurement information and the Particle serious degradation cause low estima...
Extended Kalman filter (EKF) is often employed in determining the position of mobile robot and landm...
The computational bottleneck in all informationbased algorithms for SLAM is the recovery of the stat...
This paper presents an experimentally validated alternative to the classical extended Kalman filter ...
International audienceThis paper introduces a new approach to SLAM which combines an Information Fil...
Abstract: A SLAM algorithm inspired by biological principles has been recently proposed and shown to...
This paper proposes a real-time nonlinear filtering approach for the SLAM problem, termed as compres...
Recently a SLAM algorithm based on biological principles (RatSLAM) has been proposed. It was proven ...
This paper proposes an innovative simultaneous localization and mapping (SLAM) algorithm which combi...
Designing filters exploiting the sparseness of the information matrix for efficiently solving the si...
The process of simultaneously building the map and locating a vehicle is known as Simultaneous Local...
is the development of algorithms which scale with the size of the environment. A few promising metho...
This dissertation describes the development of a method for simultaneous localization and mapping (S...
In this paper we describe the Combined Filter, a judicious combination of Extended Kalman (EKF) and ...
This electronic version was submitted by the student author. The certified thesis is available in th...
The lack of the latest measurement information and the Particle serious degradation cause low estima...
Extended Kalman filter (EKF) is often employed in determining the position of mobile robot and landm...
The computational bottleneck in all informationbased algorithms for SLAM is the recovery of the stat...
This paper presents an experimentally validated alternative to the classical extended Kalman filter ...