Universität zu Köln

Chadalavada, Ravi Teja, Andreasson, Henrik, Schindler, Maike ORCID: 0000-0001-9530-4151, Palm, Rainer and Lilienthal, Achim J. ORCID: 0000-0003-0217-9326 (2020). Bi-directional navigation intent communication using spatial augmented reality and eye-tracking glasses for improved safety in human-robot interaction. Robot. Comput.-Integr. Manuf., 61. OXFORD: PERGAMON-ELSEVIER SCIENCE LTD. ISSN 1879-2537

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Abstract

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.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Chadalavada, Ravi Teja UNSPECIFIED UNSPECIFIED UNSPECIFIED Andreasson, Henrik UNSPECIFIED UNSPECIFIED UNSPECIFIED Schindler, Maike UNSPECIFIED orcid.org/0000-0001-9530-4151 UNSPECIFIED Palm, Rainer UNSPECIFIED UNSPECIFIED UNSPECIFIED Lilienthal, Achim J. UNSPECIFIED orcid.org/0000-0003-0217-9326 UNSPECIFIED
URN:	urn:nbn:de:hbz:38-347860
DOI:	10.1016/j.rcim.2019.101830
Journal or Publication Title:	Robot. Comput.-Integr. Manuf.
Volume:	61
Date:	2020
Publisher:	PERGAMON-ELSEVIER SCIENCE LTD
Place of Publication:	OXFORD
ISSN:	1879-2537
Language:	English
Faculty:	Faculty of Human Sciences
Divisions:	Faculty of Human Sciences > Department Heilpädagogik und Rehabilitation
Subjects:	Education Mathematics
Uncontrolled Keywords:	Keywords Language FIXATIONS; STEP Multiple languages Computer Science, Interdisciplinary Applications; Engineering, Manufacturing; Robotics Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/34786