论文标题
调查机器人能力自我评估对信任和绩效的影响
Investigating the Effects of Robot Proficiency Self-Assessment on Trust and Performance
论文作者
论文摘要
人类机器人团队将很快被期望在高风险和不确定的环境中完成复杂的任务。在这里，人类可能不一定是机器人专家，而是需要建立对机器人能力的基线理解，以便适当利用和依靠机器人。这种愿意依靠（也称为信任）的意愿部分基于人类对机器人在给定任务中熟练程度的信念。如果信任太高，人类可能会将机器人推向其能力之外。如果信任太低，那么人类在原本可以拥有的情况下可能不会利用它，从而浪费宝贵的资源。在这项工作中，我们开发并执行了一项在线人类对象研究，以调查基于分解的机器自信的机器人能力自我评估报告如何在网格世界导航任务中影响操作员的信任和任务绩效。此外，我们介绍并分析了信任水平评估的度量标准，该指标可以在人类队友自由切换传送和自主控制之间进行切换时衡量操作员和机器人之间的控制分配。我们的结果表明，一份先验机器人自我评估报告将运营商的信任与机器人熟练程度保持一致，并导致绩效提高和自我报告的信任的略有提高。
Human-robot teams will soon be expected to accomplish complex tasks in high-risk and uncertain environments. Here, the human may not necessarily be a robotics expert, but will need to establish a baseline understanding of the robot's abilities in order to appropriately utilize and rely on the robot. This willingness to rely, also known as trust, is based partly on the human's belief in the robot's proficiency at a given task. If trust is too high, the human may push the robot beyond its capabilities. If trust is too low, the human may not utilize it when they otherwise could have, wasting precious resources. In this work, we develop and execute an online human-subjects study to investigate how robot proficiency self-assessment reports based on Factorized Machine Self-Confidence affect operator trust and task performance in a grid world navigation task. Additionally we present and analyze a metric for trust level assessment, which measures the allocation of control between an operator and robot when the human teammate is free to switch between teleportation and autonomous control. Our results show that an a priori robot self-assessment report aligns operator trust with robot proficiency, and leads to performance improvements and small increases in self-reported trust.
