Navigating with ranging radios: Five data sets with ground truth

Abstract

Here we present five large data sets with range-only measurements between a mobile robot and stationary nodes. Each data set consists of range measurements, surveyed locations of the stationary radio nodes, dead-reckoned trajectory of the robot, and ground truth from a sophisticated inertial navigation system/global positioning system mounted on a robot traveling several kilometers at a time. Range measurements are made with two radio-based ranging systems: a RFID tag-based ranging system and an ultra-wide band ranging system. All the data are accurately time-stamped and presented in standard formats (i.e., text files). In addition to the raw data, we present some noise characteristics of the two different ranging systems to offer insight into the quality of the range data from each system. C 2009 Wiley Periodicals, Inc.

A composite beacon initialization for EKF range-only SLAM

“…To test and compare our implementation we used two type of datasets. The first one comes from a simulation environment, whereas the second one is a publicly available experimental dataset presented in [18]. It is intended for RO-SLAM…”

“…After evaluating the behavior of our approach on a tra- jectory with different types of noise and comparing the performances with other approaches, we also wanted to test the reliability of our approach on a real dataset. [18], was realized with a mobile robot in an outdoor environment by collecting range measurements with time-of-flight UWB (Ultra Wide Band) RF beacons. The variance σ 2 i of the range measurements is set to 0.5 m 2 according to the description of the system.…”

WiFi SLAM algorithms: an experimental comparison

“…One relevant public database is the one supplied by the Robotics Institute of Carnegie Mellon University. 9 This work provides an extension to that database by collecting the indoor WiFi database described below.…”

“…Furthermore, the authors have made public the dataset described in ref. [9]. This paper proposes the use of the SAM (Smoothing And Mapping) approach to solve the RO SLAM problem.…”

Modeling mobile robot motion with polar representations

“…The system used to perform the experiments was an instrumented autonomous robot with highly accurate (2cm) positioning for ground truth using RTK GPS receivers as well as a fiber optic gyro and wheel encoders. With this setup, we collected three kinds of data: the groundtruth path of the robot from GPS and inertial sensors, the path from dead reckoning, and the range/bearing measurements to the nodes [14].…”