Article
Intuitive Spatial Tactile Feedback for Better Awareness about
Robot Trajectory during Human–Robot Collaboration
Stefan Grushko * , Aleš Vysocký , Dominik Heczko and Zdenko Bobovský
Citation: Grushko, S.; Vysocký, A.;
Heczko, D.; Bobovský, Z. Intuitive
Spatial Tactile Feedback for Better
Awareness about Robot Trajectory
during Human–Robot Collaboration.
Sensors 2021, 21, 5748. https://
doi.org/10.3390/s21175748
Academic Editors: Abolfazl Zaraki
and Hamed Rahimi Nohooji
Received: 20 July 2021
Accepted: 25 August 2021
Published: 26 August 2021
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4.0/).
Department of Robotics, Faculty of Mechanical Engineering, VSB-TU Ostrava, 70800 Ostrava, Czech Republic;
ales.vysocky@vsb.cz (A.V.); dominik.heczko@vsb.cz (D.H.); zdenko.bobovsky@vsb.cz (Z.B.)
* Correspondence: stefan.grushko@vsb.cz
Abstract:
In this work, we extend the previously proposed approach of improving mutual perception
during human–robot collaboration by communicating the robot’s motion intentions and status
to a human worker using hand-worn haptic feedback devices. The improvement is presented
by introducing spatial tactile feedback, which provides the human worker with more intuitive
information about the currently planned robot’s trajectory, given its spatial configuration. The
enhanced feedback devices communicate directional information through activation of six tactors
spatially organised to represent an orthogonal coordinate frame: the vibration activates on the side
of the feedback device that is closest to the future path of the robot. To test the effectiveness of the
improved human–machine interface, two user studies were prepared and conducted. The first study
aimed to quantitatively evaluate the ease of differentiating activation of individual tactors of the
notification devices. The second user study aimed to assess the overall usability of the enhanced
notification mode for improving human awareness about the planned trajectory of a robot. The
results of the first experiment allowed to identify the tactors for which vibration intensity was most
often confused by users. The results of the second experiment showed that the enhanced notification
system allowed the participants to complete the task faster and, in general, improved user awareness
of the robot’s movement plan, according to both objective and subjective data. Moreover, the majority
of participants (82%) favoured the improved notification system over its previous non-directional
version and vision-based inspection.
Keywords:
human–robot collaboration; human–robot interaction; mutual awareness; haptic feedback
device; human–machine interface; spatial tactile feedback
1. Introduction
Collaborative robot applications bring new possibilities for the automation of manufac-
turing processes and better adaptability of the work task in a low structured environment
through human intelligence, perception, and decision-making ability [
1
]. As a result, the
robot task and production technology can be significantly simplified since the human
worker can easily do the cognitively more demanding part. However, most of the modern
collaborative industrial applications are limited by the fact that neither collaborative side is
fully aware of the partner: the human operator may not see the robot movement due to
own engagement in the work process, and the collaborative robot simply has no means
of knowing the position of the operator. This fact may manifest in possible collisions,
which are, however, relatively safe, as the collaborative robots are lightweight and highly
sensitive to the impacts. Nevertheless, the perspective of active collision avoidance [
2
–
5
]
may represent an efficiency boost to the work process, especially in work tasks with high
variability. A collaborative workspace is a good example of a dynamic environment, where
the human worker represents an element with the highest variability. Enabling a robot
system to monitor its surroundings using range imaging sensors and enabling it to adapt
trajectories to the motions of the operator partially diminish the risk of collision. Still, it
Sensors 2021, 21, 5748. https://doi.org/10.3390/s21175748 https://www.mdpi.com/journal/sensors
