English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Human-robot teams will soon be expected to accomplish complex tasks inhigh-risk and uncertain environments. Here, the human may not necessarily be arobotics expert, but will need to establish a baseline understanding of therobot's abilities in order to appropriately utilize and rely on the robot. Thiswillingness to rely, also known as trust, is based partly on the human's beliefin the robot's proficiency at a given task. If trust is too high, the human maypush the robot beyond its capabilities. If trust is too low, the human may notutilize it when they otherwise could have, wasting precious resources. In thiswork, we develop and execute an online human-subjects study to investigate howrobot proficiency self-assessment reports based on Factorized MachineSelf-Confidence affect operator trust and task performance in a grid worldnavigation task. Additionally we present and analyze a metric for trust levelassessment, which measures the allocation of control between an operator androbot when the human teammate is free to switch between teleportation andautonomous control. Our results show that an a priori robot self-assessmentreport aligns operator trust with robot proficiency, and leads to performanceimprovements and small increases in self-reported trust.

Investigating the Effects of Robot Proficiency Self-Assessment on Trust and Performance