Published March 20, 2024 | Version v1
Dataset Open

Causal HRSI Dataset: Human-Robot Spatial Interaction Dataset for Causal Analysis from Mobile Platforms

  • 1. ROR icon University of Lincoln
  • 2. ROR icon University of Padua
  • 3. ROR icon National Research Council

Description

Causal HRSI Dataset: Human-Robot Spatial Interaction Dataset for Causal Analysis from Mobile Platforms

The dataset captures a Human-Robot Spatial Interaction (HRSI) scenario between a person and the TIAGo robot. It focuses specifically on human-goal and human-robot spatial interaction in an indoor environment, captured from the perspective of a 3D Velodyne VLP-16 LiDAR mounted on the TIAGo robot. It includes:
  • rosbags containing: Velodyne LiDAR point clound, robot and human state (position, orientation and velocities);
  • CSV files containing trajectories of the person and the robot generated by post-processing the rosbags;
  • the map of the environment extracted from the TIAGo robot.

15 participants took part in the experiment, with the dataset capturing 5 minutes of HRSI motion for each participant.

Experiment Description

The experiment and data collection occurred in a laboratory room of the University of Lincoln (UK), measuring 5 x 8.2m. 
Fifteen participants (6 females, aged between 25 and 55) took part in the experiment. Seven of them were used to work with a robot. They were required to walk between four goal positions and avoid the robot if a cross occurs. A predefined rectangular path was set for the TIAGo robot to navigate along the room and generate frequent interactions with the participants.

The experimental procedure can be described as follows. Each participant started from one of the four target positions. The next target position was randomly chosen by the participant, who then started moving towards it. Upon reaching the goal position, the participant stopped there and randomly chose the next goal, repeating the process for 5 minutes. In this experimental setting, the robot was considered by the participant as an obstacle to avoid while walking towards their target positions.

Directory Structure

Dataset
|
|____Map: folder containing the map of the environment extracted from the TIAGo robot
|
|____RosBags: forder containing the rosbag for each partipant
|        |____A1.bag
|        |____A2.bag
|        |____A3.bag
|        |____A4.bag
|        |____A5.bag
|        |____A6.bag
|        |____A7.bag
|        |____A8.bag
|        |____A9.bag
|        |____A10.bag
|        |____A11.bag
|        |____A12.bag
|        |____A13.bag
|        |____A14.bag
|        |____A15.bag
|
|____Trajectories: postprocessed trajectories extracted for the rosbag files 
         |____A1_traj.csv
         |____A2_traj.csv
         |____A3_traj.csv
         |____A4_traj.csv
         |____A5_traj.csv
         |____A6_traj.csv
         |____A7_traj.csv
         |____A8_traj.csv
         |____A9_traj.csv
         |____A10_traj.csv
         |____A11_traj.csv
         |____A12_traj.csv
         |____A13_traj.csv
         |____A14_traj.csv
         |____A15_traj.csv

Files

Dataset.zip

Files (20.8 GB)

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md5:31b9101599de7d07140f94ab8774f0f6
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Additional details

Funding

European Commission
DARKO - Dynamic Agile Production Robots That Learn and Optimise Knowledge and Operations 101017274

Software

Repository URL
https://github.com/lcastri/causal-hrsi-utils
Programming language
Python