In this paper we show that all processes associated to the move-sense-update cycle of EKF SLAM can be carried out in time linear in the number of map features. We describe Divide and Conquer SLAM, an EKF SLAM algorithm where the computational complexity per step is reduced from O(n) to O(n) (the total cost of SLAM is reduced from O(n) to O(n)). In addition, the resulting vehicle and map estimat...

Phenology is a science that fundamental to crop productivity and especially sensitive environmental changes. In Mediterranean semi-arid climates, vineyard phenology directly affected by changes in temperature rainfall distribution, being highly vulnerable climate change. Due the significant heterogeneity soil, climate, variables, we need fast reliable ways assess large areas. This research aims...

We propose a distributed cooperative positioning algorithm using the extended Kalman filter (EKF) based spatio-temporal data fusion (STDF) for wireless network composed of sparsely high-mobility nodes. Our first makes coarse estimation position and mobility state nodes by prediction step EKF. Then it utilizes estimate as prior STDF that relies on factor graph (FG), thus facilitates inferring po...

Indoor wireless localization using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. In this paper, we propose an algorithm that uses the combination of channel-separate polynomial regression model (PRM), channel-separate fingerprinting (FP), outlier detection and extended Kalman filtering (EKF) for smartphone-based indoor localizatio...

The article addresses the issue of mobile robotic platform positioning in GNSS-denied environments real-time. proposed system relies on fusing data from an Inertial Measurement Unit (IMU), magnetometer, and encoders. To get symmetrical error gauss distribution for measurement model achieve better performance, Error-state Extended Kalman Filter (ES EKF) is chosen. There are two stages vector sta...

This paper describes a method for sensor pose estimation, as well creating large-scale 3D maps, construction cranes equipped with system consisting of camera, 2D lidar, and IMU. To tackle the challenges posed by crane boom’s complex motion, we utilize an Extended Kalman filter (EKF) to improve accuracy reliability estimation. By combining estimates from Visual-Inertial Navigation System (VINS) ...