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Univ.-Prof. Dr.-Ing. Horst-Michael Groß
Head of Department
e-mail: fg-nikr@tu-ilmenau.de
phone: +49 3677 692858
Postal address:
Ilmenau University of Technology
Faculty of Computer Science and Automation
Neuroinformatics and Cognitive Robotics Lab
P.O. Box 10 05 65
98684 Ilmenau
Visiting address:
Helmholtzplatz 5 (Zusebau)
Room 3060
98693 Ilmenau
Site plan
As a base for training models able to predict exact position of doors' hinges and indirectly the position of the door handles we recorded a dataset of different doors in the wild. Aim was to enable robotic manipulation of doors from arbitrary opening state. While we concentrate on solving the localization problem by means of laser range scan data, we additionally recorded RGB-D data as well.
This dataset conists of raw laser range scans of doors taken with a SICK S300 in a height of 20cm over ground. Each door was recorded from both sides (if possible) at three different recording positions of about 1m away from the left door frame, the middle of the door, and the right door frame. There were doors of 7 different buildings, either office and lecture halls of the university or private homes.
In order to overcome the noise of the laser range scanner SICK S300, we averaged 30 scans which is possible because we are in a steady position. Furthermore, the door was recorded in different opening angles ranging form closed state, over unlatched (~ 0-15 deg), over partly open (~ 15-70 deg), to fully open (~ 90 deg). The Labels of the state have been set by eye.
While recording the raw scans we also marked the ground truth hinge, lock, and corner frames in the range scan coordinates. The figure shows all parameters describing the door’s geometry and position in the world.
Additionally, there was a Kinect Azure camera placed at a height of ~ 1.2m coarsly over the SICK. For each sample a depth image and a color image have been recorded. The transformation of the camera to the laser scanner has been manually annotated by aligning the range scan and the points of the central depth image line (these were used as a virtual range scan).
There are two versions for download. First is the complete dataset including the images, while the second version only comprises the range scans and therefore is much smaller.
The raw data in the respective .zip files consists of separate files for each sample:
The door parameters like opening direction and state are provided in the Dataset.csv file, which contains one row for each sample.
The columns are as follows:
ID | running number |
color intrinsic | filename of the color_intrinsic file for that sample |
depth intrinsic | filename of the belonging depth intrinsic file |
color image | the filename of the belonging color image |
depth image | the filename of the belonging depth image |
transforms file | filename of the respective transforms.xml file with all the postition annotations |
Door State | 1- closed, 2- unlatched, 3- partly open, 4- fully open |
Opening Direction | 0- left, 1- right |
RangeScan file | filename of the belonging rangescan.xml file |
DepthInside | distance of visible door line to lock hinge baseline [m] |
DepthOutside | distance of visible door line to lock hinge baseline [m] |
DoorWidth | distance of hinge and lock [m] |
BoardWidthInside | width of the door panel on inside [m] |
BoardWidthOutside | width of the door panel on outside [m] |
HingeOffset | distance of hinge to the border of the panel on inside |
DoorID | instance id for each door |
If you consider using the data sets on this page, please reference the following:
Müller, St., Müller, T., Aamir, A., Gross, H.-M.
Laser-Based Door Localization for Autonomous Mobile Service Robots.
in: Sensors 23 (2023), no. 11, 5247; https://doi.org/10.3390/s23115247
To get access via FTP, please send the completed form by email to nikr-datasets-request@tu-ilmenau.de (for research purposes only).