Data Set htwddKogRob-TSDReal for Localization and Lifelong Mapping

This dataset represents a 4.7 km long tour (odometry path shown in htwddKogRob-TSDReal_path.png) in an environment whose representation (see map htwddKogRob-TSDReal.png | 1px \(\widehat{=}\) 0.1m) is now obsolete. Several static objects have been moved or removed, and there are varying numbers of dynamic obstacles (people walking around).

The work was first presented in:

A Fuzzy-based Adaptive Environment Model for Indoor Robot Localization

Authors: Frank Bahrmann, Sven Hellbach, Hans-Joachim Böhme

Date of Publication: 2016/10/6

Conference: Telehealth and Assistive Technology / 847: Intelligent Systems and Robotics

Publisher: ACTA Press

Additionally, we present a video with the proposed algorithm and an insight of this dataset under:

youtube.com/AugustDerSmarte

https://www.youtube.com/watch?v=26NBFN_XeQg

Instructions for use

The zip archive contains ascii files, which hold the log files of the robot observations and robot poses. Since this data set was recorded in a real environment, the logfiles hold only the odometry based robot poses. For further information, please refer to the header of the logfiles. To simplify the parsing of the files, you can use these two Java snippets:

Laser Range Measurements:

List ranges = new ArrayList<>(numOfLaserRays);
List errors = new ArrayList<>(numOfLaserRays);

String s = line.substring(4);
String delimiter = "()";
StringTokenizer tokenizer = new StringTokenizer(s, delimiter);

while(tokenizer.hasMoreElements()){
String[] arr = tokenizer.nextToken().split(";");
boolean usable = (arr[0].equals("0")?false:true);
double range = Double.parseDouble(arr[1]);

ranges.add(range);
errors.add(usable?Error.OKAY:Error.INVALID_MEASUREMENT);
}

Poses:

String poseString = line.split(":")[2];
String[] elements = poseString.substring(1, poseString.length()-1).split(";");
double x = Double.parseDouble(elements[0]);
double y = Double.parseDouble(elements[1]);
double phi = Double.parseDouble(elements[2]);