DOI: 10.5281/zenodo.8224067
title: Benchmark movement data set for trust assessment in human robot collaboration

description: In the Drapebot project, a worker is supposed to collaborate with a large industrial manipulator in two tasks: collaborative transport of carbon fibre patches and collaborative draping. To realize data-driven trust assessement, the worker is equipped with a motion tracking suit and the body movement data is labeled with the trust scores from a standard Trust questionnaire (Trust perception scale - HRI, Schaefer 2016).


Data has been collected in the transport and draping tasks (counterbalanced) from 20 participants,  7 female and 13 male, average age 25 (SD = 4.0). Average height was 1.74 meters (SD = 0.1). One session consists of 24 trials on average for the transport and draping task resulting in 951 trials across all conditions. For all sessions, body tracking was performed using the Xsens MVN Awinda tracking suit. It consists of a tight-fitting shirt, gloves, headband, and a series of straps used to attach 17 IMUs to the participant. After calibration the system uses inverse kinematics to track and log the movements of the participant at a rate of 60 Hz. The measurements include linear and angular speed, velocity, and acceleration of every skeleton tracking point (see XSENS manual for a detailed description of avaiable measurements).


Data organization


There are 20 files for 20 participants of each task accordingly (transport and draping). The name of the files is P01SD, where the number 01 is the participant the D stands for draping. Accordingly, P01ST stands for transport. Each file contains all the data that was generated from the XSENS motion capture system. The files are xlsx files and for each sheet inside the excel file there are different types of data:



	
Segment Orientation - Quat
	
Segment Orientation - Euler
	
Segment Position
	
Segment Velocity
	
Segment Acceleration
	
Segment Angular Velocity
	
Segment Angular Acceleration
	
Joint Angles ZXY
	
Joint Angles XZY
	
Ergonomic Joint Angles ZXY
	
Ergonomic Joint Angles XZY
	
Center of Mass
	
Sensor Free Acceleration
	
Sensor Magnetic Field
	
Sensor Orientation - Quat
	
Sensor Orientation - Euler



See also: https://base.movella.com/s/article/Output-Parameters-in-MVN-1611927767477?language=en_US


For more information on each specific data and/or sensors please see the xsens manual (Link above)


Data Annotation


For each procedure there is an annotation file called sorted_draping.xlsx and sorted_transport.xlsx. In these files the first column is the frame and from column 2 until column 21 are the annotations for each procedure for each participant. The annotations describe the different phases during the procedures for each data frame recorded by xsens:



	
Transport phases: pick, transport, drop, return
	
Draping phases: approach, draping, return



The file trustscores.xlsx includes some demographic data as well as the results of the trust questionaire for each participant and each task, including the scores for the individual items as well as the calculated trust score. The different columns are:



	
Subject: participant number for crossreferencing with annotation and movement data
	
Transport.Speed: denoting the robot speed (fast or slow)
	
Age: age of the participant
	
Gender: gender of the participant
	
DominantHand: dominant hand of the participant (left or right)
	
Height: height of the participant
	
Score for answers of the participant in related questions category.



This is followed by the trust questionaire items:



	
Which % of time does the robot
	

		
Function successfully
		
Act consistently
		
Communicate with people
		
Provide feedback
		
Malfunction
		
Follow directions
		
Meet the needs of the mission
		
Perform exactly as instructed
		
Have errors
	
	
	
Which % of the time is the robot:
	

		
Unresponsive
		
Dependable
		
Reliable
		
Predictable
	
	



The last two columns are



	
TrustScore – Final trust score calculated from all questions
	
Task – Which task is being performed (Transport/Draping)