last modified

2016-01-05

nickname

rss

institution

KTH - Royal Institute of Technology

reason for most recent change

the initial version

release date

2016-01-05

website

www.crawdad.org/kth/rss

network type

sensor network

network type

802.11 ad-hoc

network type

802.11 infrastructure

collection environment

The indoor data was collected at the 5th floor of one of KTH's office building (Teknikringen 14, 10044 Stockholm) during working hours.

The outdoor data was collected at an abandoned steel factory in Dortmund (Phoenix-West), Germany during an Evaluation exercise of TRADR project (http:\/\/www.tradr-project.eu\/).

network configuration

IEEE 802.11n Wi-Fi 2.4GHz network was used in the dataset.

data collection methodology

The RSS was collected using the RSSI metric in dBm. The mobile robot data such as position and orientation was collected with the help of Robot Operating System (ROS) drivers of the respective robot.

• Ramviyas Parasuraman
  ramviyas@kth.se
  Computer Vision and Active Perception Lab., Centre for Autonomous Systems, School of Computer Science and Communication, Royal Institute of Technology (KTH), Stockholm, Sweden
  
• Sergio Caccamo
  caccamo@kth.se
  Computer Vision and Active Perception Lab., Centre for Autonomous Systems, School of Computer Science and Communication, Royal Institute of Technology (KTH), Stockholm, Sweden
  
• Fredrik Baberg
  fbaberg@kth.se
  Computer Vision and Active Perception Lab., Centre for Autonomous Systems, School of Computer Science and Communication, Royal Institute of Technology (KTH), Stockholm, Sweden
  
• Petter Ogren
  petter@kth.se
  Computer Vision and Active Perception Lab., Centre for Autonomous Systems, School of Computer Science and Communication, Royal Institute of Technology (KTH), Stockholm, Sweden
  

The following papers are written by the providers of this dataset who may be able to provide more information:

• Extending a UGV teleoperation FLC interface with wireless network connectivity information
  Sergio Caccamo; Ramviyas Parasuraman; Fredrik Baberg; Petter Ogren;
  In Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on (2015), pp. 4305-4312, doi:10.1109/iros.2015.7353987.

12 papers using this dataset can be found in our CiteULike library.

When writing a paper that uses CRAWDAD datasets, we would appreciate it if you could cite both the authors of the dataset and CRAWDAD itself, and identify the exact dataset using the appropriate version number. For this dataset, this citation would look like:

Ramviyas Parasuraman, Sergio Caccamo, Fredrik Baberg, Petter Ogren, CRAWDAD dataset kth/rss (v. 2016‑01‑05), downloaded from https://crawdad.org/kth/rss/20160105, https://doi.org/10.15783/C7088F, Jan 2016.

• Cite using BibTeX
• Cite using RIS

@misc{kth-rss-20160105,
    author = {Ramviyas Parasuraman and Sergio Caccamo and Fredrik Baberg and Petter Ogren},
    title = {{CRAWDAD} dataset kth/rss (v. 2016-01-05)},
    howpublished = {Downloaded from \url{https://crawdad.org/kth/rss/20160105}},
    doi = {10.15783/C7088F},
    month = jan,
    year = 2016
}

TY  - DATA
TI  - CRAWDAD dataset kth/rss (v. 2016-01-05)
UR  - https://crawdad.org/kth/rss/20160105
PY  - 2016/01/05/
AU  - Ramviyas Parasuraman
AU  - Sergio Caccamo
AU  - Fredrik Baberg
AU  - Petter Ogren
DO  - 10.15783/C7088F
ER  -

If you do not use the provided citation formats, please include a reference with the same information, as described in the CRAWDAD FAQ.