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View all- Damodaran DDamodaran SThiyagarajan MSrinivasan L(2024)Forging TrustUsing Real-Time Data and AI for Thrust Manufacturing10.4018/979-8-3693-2615-2.ch003(43-71)Online publication date: 10-May-2024
Increasing user trust in a fetching robot using explainable AI in a traded control paradigm
Article No.: 9, Pages 1 - 8
Abstract
Recently, there has been an increase use of collaborative robots in manufacturing, healthcare, military, and personal use scenarios. Such robots operate under shared or traded control paradigms with their human operators or users. Therefore, it is important to understand how to address and improve issues of trust between the humans and collaborative robots. In this paper, we investigate the impact of robotic agent transparency to their subjective trust level by a human operator. Several experiments were conceived with the help of a fetching mobile robot under traded control, and data such as subjective trust level was collected during experimentation. Results indicate that trust is easier to lose than it is to gain. Furthermore, results also indicate that agent transparency's effect on operator trust is more significant in tasks of increasing complexity.
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- Increasing user trust in a fetching robot using explainable AI in a traded control paradigm
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Published: 30 June 2020
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PETRA '20: The 13th PErvasive Technologies Related to Assistive Environments Conference
June 30 - July 3, 2020
Corfu, Greece
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View all- Damodaran DDamodaran SThiyagarajan MSrinivasan L(2024)Forging TrustUsing Real-Time Data and AI for Thrust Manufacturing10.4018/979-8-3693-2615-2.ch003(43-71)Online publication date: 10-May-2024
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