Dataset Open Access

THOR - point clouds

Andrey Rudenko; Tomasz Piotr Kucner; Chittaranjan Sriniva Swaminathan SWAMINATHAN; Ravi Teja Chadalavada; Kaj O. Arras; Achim J. Lilienthal

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<oai_dc:dc xmlns:dc="" xmlns:oai_dc="" xmlns:xsi="" xsi:schemaLocation="">
  <dc:creator>Andrey Rudenko</dc:creator>
  <dc:creator>Tomasz Piotr Kucner</dc:creator>
  <dc:creator>Chittaranjan Sriniva Swaminathan SWAMINATHAN</dc:creator>
  <dc:creator>Ravi Teja Chadalavada</dc:creator>
  <dc:creator>Kaj O. Arras</dc:creator>
  <dc:creator>Achim J. Lilienthal</dc:creator>
  <dc:description>THÖR is a dataset with human motion trajectory and eye gaze data collected in an indoor environment with accurate ground truth for the position, head orientation, gaze direction, social grouping and goals. THÖR contains sensor data collected by a 3D lidar sensor and involves a mobile robot navigating the space. In comparison to other, our dataset has a larger variety in human motion behaviour, is less noisy, and contains annotations at higher frequencies.

The dataset includes 9 separate recordings in 3 variations:

	``One obstacle" - features one obstacle in the environment and no robot
	``Moving robot" - features one obstacle in the environment and the moving robot
	``Three obstacles" - features three obstacles in the environment and no robot

THOR - point clouds is the part of THÖR data set containing bag files with 3D scans collcted during the experiments.


For more details check project website or check our publications:

title={TH\"OR: Human-Robot Indoor Navigation Experiment
and Accurate Motion Trajectories Dataset},
author={Andrey Rudenko and Tomasz P. Kucner and
Chittaranjan S. Swaminathan and Ravi T. Chadalavada
and Kai O. Arras and Achim J. Lilienthal},
journal={arXiv preprint arXiv:1909.04403},
  <dc:subject>Human Robot Interaction</dc:subject>
  <dc:subject>Motion Prediction</dc:subject>
  <dc:subject>Social Robotics</dc:subject>
  <dc:subject>People Tracking</dc:subject>
  <dc:subject>Range data</dc:subject>
  <dc:title>THOR - point clouds</dc:title>
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