Abstract
In this work, a comparative study between an Ultra Wide-Band (UWB) localization system and a Simultaneous Localization and Mapping (SLAM) algorithm is presented. Due to its high bandwidth and short pulses length, UWB potentially allows great accuracy in range measurements based on Time of Arrival (TOA) estimation. SLAM algorithms recursively estimates the map of an environment and the pose (position and orientation) of a mobile robot within that environment. The comparative study presented here involves the performance analysis of implementing in parallel an UWB localization based system and a SLAM algorithm on a mobile robot navigating within an environment. Real time results as well as error analysis are also shown in this work.
Highlights
This article addresses the experimental comparison analysis between an ultra wide-band localization system (UWB) and a SLAM (Simultaneous Localization and Mapping) algorithm.Indoor location systems have some problems such as the ability to locate objects exactly
In P2, the system acquires again several measurements. Those measurements associated with a same position are used to build the uncertainty ellipse associated with a given position of the mobile robot. As it can be seen, the path estimated by the SLAM algorithm (Figure 12(c)) shows a better path—from a covariance perspective—than the path obtained by the UWB localization system
The experimental results show that both localization systems can be used to localize mobile robots in indoor environments with high accuracy
Summary
This article addresses the experimental comparison analysis between an ultra wide-band localization system (UWB) and a SLAM (Simultaneous Localization and Mapping) algorithm. The UWB localization system and the SLAM algorithm are implemented in parallel on a mobile robot. The mobile robot is equipped with an UWB receiver that estimates the robot localization measuring the Time Difference of Arrival (TDOA) between pairs of synchronized base stations. The estimation of the ranges between base stations and robot’s current position (see Equation 3) is performed by multiplying the estimated time difference with the radio speed (4). These ranges produce a set of hyperbolas and their intersections determine the MR position.
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