‘I’m Confident This Will End Poorly’: Robot Proficiency Self-Assessment in Human-Robot Teaming
Published in IEEE International Conference on Intelligent Robots and Systems (IROS), 2022
Recommended citation: N. Conlon, D. Szafir, and N. Ahmed. "I’m Confident This Will End Poorly": Robot Proficiency Self-Assessment in Human-Robot Teaming. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). October 2022. https://ieeexplore.ieee.org/document/9981653
Abstract: Human-robot teams are expected to accomplish complex tasks in high-risk and uncertain environments. In domains such as space exploration or search & rescue, a human operator may not be a robotics expert, but will need to establish a baseline understanding of the robot’s capabilities with respect to a given task in order to appropriately utilize and rely on the robot. This willingness to rely, also known as trust, is based partly on the operator’s belief in the robot’s task proficiency. If trust is too high, the operator may unknowingly push the robot beyond its capabilities. If trust is too low, the operator may not utilize it when they otherwise could have, wasting precious time and resources. In this work, we discuss results from an online human-subjects study investigating how a robot communicated report of its task proficiency with respect to an operator’s expectations affects trust and performance in a navigation task. Our results show that communication of a robot self-assessment helped operators understand when reliance on the robot was appropriate given the task and conditions. This led to improvements in task performance, informed choices of autonomy level, and increased trust.