Localization forms the heart of various autonomous mobile robots. For efficient navigation,
these robots need to adopt effective localization strategy. This paper, presents a …

Localization plays an important role in the field of Wireless Sensor Networks (WSNs) and
robotics. Currently, localization is a very vibrant scientific research field with many potential …

Purpose–The main purpose of this paper is to investigate two key elements of localization
and mapping of Autonomous Underwater Vehicle (AUV), ie to overview various sensors and …

This paper presents an experimentally validated alternative to the classical extended
Kalman filter approach to the solution of the probabilistic state-space simultaneous …

This paper introduces a square root unscented Kalman filter (SRUKF) solution to the
problem of performing visual simultaneous localization and mapping (SLAM) using a single …

This paper addresses two key limitations of the unscented Kalman filter (UKF) when applied
to the simultaneous localization and mapping (SLAM) problem: the cubic computational …

This paper develops a square root unscented Kalman filter (SRUKF) for performing video-
rate visual simultaneous localization and mapping (SLAM) using a single camera. The …

The growing interest and use of indoor mapping is driving a demand for improved data-
acquisition facility, efficiency and productivity in the era of the Building Information Model …

This paper addresses two key limitations of the unscented Kalman filter (UKF) when applied
to the simultaneous localization and mapping (SLAM) problem: the cubic, in the number of …

In this paper, we address the problem of uncertainty propagation through nonlinear
stochastic dynamical systems. More precisely, given a discrete-time continuous-state …