This page hosts a collection of data sets and utilities for evaluating multisensor pedestrian navigation algorithms.
Visit the place where the data sets were recorded at Google Earth [
KMZ].
Measurement data
Please find detailed information on the dataformats
here.
The files include measurement data from the IMUs (inertial measurement units), GPS, RFIDs, Altimeter, Compass, GTRP timestamps (reference points timestamps), GTRP names/sequence
| Sensors |
Data set |
Comment |
|
All sensors
|
March09Measurement03.zip
|
This data set starts from outside the building with good GPS coverage
and already acquired GPS-receiver. After a short walk the person enters the office building. The
person then walks through the corridor in the lower floor and subsequently climbs the stairs to the
second floor. After a similar walk on the second floor, the person reaches the elevator. The elevator
goes up to the third floor (picking up another passenger), then goes down to the garage level. The
person leaves the elevator and then performs a short meandering walk in the garage. Finally the person
leaves the garage via the ramp and returns to the starting position.
|
|
All sensors except for baro-altimeter
|
March09Measurement05.zip
|
This pure 1D data set starts from outside the building with good GPS coverage
and already acquired GPS-receiver. After a short walk the person enters the office building. The
person then walks two laps through the corridors in the ground floor whilst entering some of the offices.
Finally the person leaves the building and returns to the starting position.
|
Infrastructure data (walls, positions of RFID-tags, positions of ground truth reference points)
Matlab utilities
| Results by |
Data set |
File |
Comment |
| DLR |
March09Measurement03 |
DLR_Results_March09Measurement03_v1.0.zip |
The results compare a particle filter and an extended Kalman filter using GPS, compass, baro-altimeter, one of the foot-mounted IMUs, and the floor plan. The results comprise
the magnitude of the horizontal error at the passed GTRPs, the accompanying MATLAB script reads the data and plots it. |
| DLR |
March09Measurement05 |
DLR_Results_March09Measurement05_v1.0.zip |
The results compare a particle filter and an extended Kalman filter using GPS, compass, one of the foot-mounted IMUs, and the floor plan. The results comprise
the magnitude of the horizontal error at the passed GTRPs, the accompanying MATLAB script reads the data and plots it. |
- Create an arbitrary folder DIR
- Create two subfolders DIR/DataInfrastructure and DIR/DataMeasurement
- Download all infrastructure data files to DIR/DataInfrastructure
- Download zipfile with measurement data and unzip to DIR/DataMeasurement
- Download Matlab demo scripts and unzip to DIR. This will create subfolders DIR/Tools, DIR/@FileReader and several matlab files at DIR
- Download and extract Guillaume Flandin's XML Parser from MatlabCentral into DIR
- Start Matlab
- Within Matlab change the Current Directory to DIR
- Within Matlab start Demo.m from the command line. The demo file visualize floor plans, RFIDs locations, Reference Points locations, GPS measurements and a tick when each Reference Point is reached.
TBD
References
M. Angermann, A. Friese, M. Khider, B. Krach, K. Krack, P. Robertson
A Reference Measurement Data Set for Multisensor Pedestrian Navigation with Accurate Ground Truth [PDF]
European Navigation Conference (ENC-GNSS 2009), Naples, Italy, May 2009
Disclaimer
DLR and the authors of this software accept no responsibility for damages resulting from the use of this product and make no warranty or representation, either express or implied, including but not limited to, any implied warranty of merchantability or fitness for a particular purpose. This software is provided "AS IS", and you, its user, assume all risks when using it.