THOR - point clouds

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.

Reference:

For more details check project website thor.oru.se or check our publications:

@article{thorDataset2019,
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},
year={2019}
}

THÖR是一款采集自室内环境的数据集，收录人体运动轨迹与眼动注视数据，并配备精准的位置、头部朝向、注视方向、社交群组与目标的真实标注（ground truth）。该数据集包含由三维激光雷达（3D lidar）采集的传感器数据，场景涵盖移动机器人在空间内的导航过程。相较于其他同类数据集，THÖR的人体运动行为类型更为丰富，噪声水平更低，且标注频率更高。

该数据集包含3种变体下的9组独立录制样本：
- 「单障碍物场景」：环境中仅存在一处障碍物，无移动机器人参与
- 「移动机器人场景」：环境中存在一处障碍物，并包含移动机器人导航环节
- 「三障碍物场景」：环境中存在三处障碍物，无移动机器人参与

THOR点云（THOR - point clouds）为THÖR数据集的子集，包含实验过程中采集三维扫描数据的bag文件。

参考文献：
如需获取更多细节，可访问项目官网thor.oru.se，或查阅以下学术成果：
@article{thorDataset2019,
title={THÖR: 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},
year={2019}
}