Type of Publication: Article in Collected Edition

Adaptive DoF: Concepts to Visualize AI-generated Movements in Human-Robot Collaboration

Author(s):

Pascher, Max; Kronhardt, Kirill; Franzen, Til; Gerken, Jens

Title of Anthology:

Proceedings of the 2022 International Conference on Advanced Visual Interfaces (AVI 2022)

Publisher:

ACM

Location(s):

NewYork, NY, USA

Publication Date:

2022

ISBN:

978-1-4503-9719-3/22

Keywords:

cobot, human-robot collaboration, intention feedback, neural network, visualization techniques

Digital Object Identifier (DOI):

doi:10.1145/3531073.3534479

Citation:

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Abstract

Nowadays, robots collaborate closely with humans in a growing number of areas. Enabled by lightweight materials and safety sensors , these cobots are gaining increasing popularity in domestic care, supporting people with physical impairments in their everyday lives. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior. This, however, is crucial for achieving trust and user acceptance. One significant aspect of predicting cobot behavior is understanding their motion intent and comprehending how they "think" about their actions. We work on solutions that communicate the cobots AI-generated motion intent to a human collaborator. Effective communication enables users to proceed with the most suitable option. We present a design exploration with different visualization techniques to optimize this user understanding, ideally resulting in increased safety and end-user acceptance.