This dataset provides log files recorded in a changed indoor environment with 18 dynamic obstacles. The changes from the original map to the simulated world are highlighted in the figure htwddKogRob-TSDChangesSim_changesHighlighted.png. The total distance travelled in this data set is 179.8 km. The prior knowledge map the robot got to localize and update is shown in htwddKogRob-TSDChangesSim_prior.png and the simulated now changed map is shown in htwddKogRob-TSDChangesSim_groundTruth.png (for both maps: 1px \(\widehat{=}\) 0.1m). 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 archives contain ascii files, which hold the log files of the robot observations and robot poses. Since this data set was recorded in a simulated environment, the logfiles include both a changed starting position and a ground-truth pose. For further information, please refer to the header of the logfile. 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]); ; For further questions please contact frank.bahrmann@htw-dresden.de
Data Set htwddKogRob-TSDChangesSim for Localization and Lifelong Mapping
2016-10-06
Research Data
Electronic Resource
English
DDC: | 629 |
Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping Through Continual Learning
Springer Verlag | 2023
|Online Contents | 2003
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