Trust-Preserved Human-Robot Shared Autonomy enabled by Bayesian Relational Event Modeling

TL;DR

This paper introduces a Bayesian relational event modeling approach to dynamically infer human trust in shared autonomy robots, enabling robots to adapt their autonomy levels to improve team performance and trust over time.

Contribution

It presents a novel trust-preserved shared autonomy strategy that actively manages human trust, enhancing robot acceptance and effectiveness in collaborative tasks.

Findings

Improved task performance in search and rescue scenarios.

Enhanced user trust and acceptance compared to baseline methods.

Effective dynamic trust inference using Bayesian relational event modeling.

Abstract

Shared autonomy functions as a flexible framework that empowers robots to operate across a spectrum of autonomy levels, allowing for efficient task execution with minimal human oversight. However, humans might be intimidated by the autonomous decision-making capabilities of robots due to perceived risks and a lack of trust. This paper proposed a trust-preserved shared autonomy strategy that allows robots to seamlessly adjust their autonomy level, striving to optimize team performance and enhance their acceptance among human collaborators. By enhancing the relational event modeling framework with Bayesian learning techniques, this paper enables dynamic inference of human trust based solely on time-stamped relational events communicated within human-robot teams. Adopting a longitudinal perspective on trust development and calibration in human-robot teams, the proposed trust-preserved shared autonomy strategy warrants robots to actively establish, maintain, and repair human trust, rather than merely passively adapting to it. We validate the effectiveness of the proposed approach through a user study on a human-robot collaborative search and rescue scenario. The objective and subjective evaluations demonstrate its merits on both task execution and user acceptability over the baseline approach that does not consider the preservation of trust.