The proposed framework decomposes the SLAM problem into a traditional SLAM problem for the static landmarks and individual SLAM problems for the dynamic landmarks. Therefore, in the dynamic environments, it is able to minimize the error caused by the dynamic landmarks and reduce the uncertainty ...
Inconsistency is a fundamental problem in simultaneous localization and mapping (SLAM). Previous works from predecessors have studied the inconsistent problem of extended Kalman filter (EKF) SLAM algorithm focusing on the linearization errors. In this paper, we studied the inconsistency issue of EKF SLA...
Development of a SIFT based monocular EKF-SLAM algorithm for a small unmanned aerial vehicle. In: SICE Annual Conference (SICE), 2011 Proceedings of; 2011. p.1656-1659.T. Suzuki, Y. Amano, and T. Hashizume. Development of a sift based monocular ekf-slam algorithm for a small u...
This paper address the Simultaneous Localization and Mapping (SLAM) problem of an AUV using bathymetric maps. The algorithm compounds swath profiles of the seafloor with DVL navigation(dead-reckoning) to build surface patches (3D point clouds). An initial guess of the location of these point cloud...
This repository contains my implementation of feature-based EKF SLAM with unsupervised learning. I implemented all the packages from Scratch using ROS in C++. Please visit my website for more information about this project. For further information about the packages, classes, and methods used in th...
《MME-EKF-based path-tracking control of autonomous vehicles considering input saturation》是期刊《IEEE Transactions on Vehicular Technology》在2019年第68卷第6期上刊载的一篇论文。《IEEE Transactions on Vehicular Technology》的中科院大类分区(工程技术)是2区,小类分区(运输科技)2区,2019年影响因子为5.379。
aAlthough EKF remains to be a popular choice for the solution of SLAM problem, as a result of the experiments in this study, UKF-based FastSLAM is observed to be the most efficient algorithm among standard EKF, UKF, FastSLAM 2.0, and uFastSLAM. 虽然EKF保持是一个普遍的选择为响声问题的解答...
A Simultaneous Localization and Mapping (SLAM) algorithm based on Gray-EKF was designed by using gray prediction theory and EKF in order to improve the accuracy of SLAM for intelligent agricultural vehicle. A GM(1,1) prediction model of observation based on improved sliding window gray prediction...
Simultaneous localization and mapping (SLAM) problem is an attractive topic in the mobile vehicle research. It is a navigation algorithm essentially. Extended Kalman Filter (EKF) is the most popular implementation to solve the SLAM problem for its simpleness and effectiveness. But the linearization ...
aThe performance of Extended Kalman Filter SLAM, Unscented Kalman Filter SLAM, EKF-based FastSLAM version 2.0, and UKF-based FastSLAM algorithms are compared in terms of accuracy of state estimations for localization of a robot and mapping of its environment. 延长的Kalman过滤器响声表现, Unscented ...