oru.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Bi-directional navigation intent communication using spatial augmented reality and eye-tracking glasses for improved safety in human-robot interaction
Örebro University, School of Science and Technology. (Centre for Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0002-8380-4113
Örebro University, School of Science and Technology. (Centre for Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0002-2953-1564
Faculty of Human Sciences, University of Cologne, Germany.
Örebro University, School of Science and Technology. (Centre for Applied Autonomous Sensor Systems (AASS))
Show others and affiliations
2020 (English)In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 61, article id 101830Article in journal (Refereed) Published
Abstract [en]

Safety, legibility and efficiency are essential for autonomous mobile robots that interact with humans. A key factor in this respect is bi-directional communication of navigation intent, which we focus on in this article with a particular view on industrial logistic applications. In the direction robot-to-human, we study how a robot can communicate its navigation intent using Spatial Augmented Reality (SAR) such that humans can intuitively understand the robot's intention and feel safe in the vicinity of robots. We conducted experiments with an autonomous forklift that projects various patterns on the shared floor space to convey its navigation intentions. We analyzed trajectories and eye gaze patterns of humans while interacting with an autonomous forklift and carried out stimulated recall interviews (SRI) in order to identify desirable features for projection of robot intentions. In the direction human-to-robot, we argue that robots in human co-habited environments need human-aware task and motion planning to support safety and efficiency, ideally responding to people's motion intentions as soon as they can be inferred from human cues. Eye gaze can convey information about intentions beyond what can be inferred from the trajectory and head pose of a person. Hence, we propose eye-tracking glasses as safety equipment in industrial environments shared by humans and robots. In this work, we investigate the possibility of human-to-robot implicit intention transference solely from eye gaze data and evaluate how the observed eye gaze patterns of the participants relate to their navigation decisions. We again analyzed trajectories and eye gaze patterns of humans while interacting with an autonomous forklift for clues that could reveal direction intent. Our analysis shows that people primarily gazed on that side of the robot they ultimately decided to pass by. We discuss implications of these results and relate to a control approach that uses human gaze for early obstacle avoidance.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 61, article id 101830
Keywords [en]
Human-robot interaction (HRI), Mobile robots, Intention communication, Eye-tracking, Intention recognition, Spatial augmented reality, Stimulated recall interview, Obstacle avoidance, Safety, Logistics
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:oru:diva-78358DOI: 10.1016/j.rcim.2019.101830ISI: 000496834800002Scopus ID: 2-s2.0-85070732550OAI: oai:DiVA.org:oru-78358DiVA, id: diva2:1374911
Note

Funding Agencies:

KKS SIDUS project AIR: "Action and Intention Recognition in Human Interaction with Autonomous Systems"  20140220

H2020 project ILIAD: "Intra-Logistics with Integrated Automatic Deployment: Safe and Scalable Fleets in Shared Spaces"  732737

Available from: 2019-12-03 Created: 2019-12-03 Last updated: 2020-02-06Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Chadalavada, Ravi TejaAndreasson, HenrikPalm, RainerLilienthal, Achim J.

Search in DiVA

By author/editor
Chadalavada, Ravi TejaAndreasson, HenrikPalm, RainerLilienthal, Achim J.
By organisation
School of Science and Technology
In the same journal
Robotics and Computer-Integrated Manufacturing
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 137 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf