An Empirical Investigation of Intelligent Disobedience for Mitigating Human Error in Collaborative Teleoperation
Bibliographic Data
| ID | 22190598 |
|---|---|
| Authors | Kavyaa Somasundaram (0000-0002-3624-0845, Örebro University), Fjollë Novakazi (0000-0001-6381-2346, Örebro University), Amy Loutfi (0000-0002-3122-693X, Örebro University) |
| Year | 2026 |
| Volume | 15 |
| Issue | 3 |
| Pages | 1-36 |
| Publication date | 2026-05-31 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ACM Transactions on Human-Robot Interaction (JOURNAL) |
| Journal identifiers | ISSN: 2573-9522 • E-ISSN: 2573-9522 |
| Publisher | Association for Computing Machinery (ACM) (PUBLISHER) |
| DOI | 10.1145/3799986 |
| OpenAlex | W7133233366 |
| Language | EN |
| References cited | 51 |
Human-induced errors—such as slips, lapses and mistakes—are natural and often unavoidable, posing significant safety risks in teleoperation, particularly in high-risk, dynamic environments like underwater operations. While previous work has emphasised system-level enhancements, the proactive mitigation of human-induced errors through empirical evaluation remains underexplored. This work presents the first empirical investigation of Intelligent Disobedience (ID) as a collaborative strategy for mitigating human errors in teleoperation. A semi-controlled, game-based Wizard-of-Oz study with 40 participants performing an underwater navigation task was conducted. Two ID strategies were evaluated: one with automatic robot mitigation and another with user-mediated robot mitigation following the disobedient intervention. Using a mixed-methods approach that triangulated quantitative performance metrics with qualitative insights from semi-structured interviews, the study examined the effects of these strategies on operator performance, acceptance, and error-mitigation outcomes across different error types. The results revealed no detectable performance degradation under ID and emphasised that human error types differ in their characteristics, necessitating the adaptation of ID intervention strategies. These findings underscore the importance of context-adaptive approaches when integrating ID into collaborative teleoperation systems
Empirical research · Human error · Human–robot interaction · Robot · Teleoperation · Tactile and Sensory Interactions · Teleoperation and Haptic Systems · Underwater Vehicles and Communication Systems
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Wizard of Oz Studies in HRI
Trust in Automation
Toward a Framework for Levels of Robot Autonomy in Human-Robot Interaction
A comparison of the Two One-Sided Tests Procedure and the Power Approach for assessing the equivalence of average bioavailability
Human–Robot Interaction
Thematic analysis
The Journey or the Destination
Sari
Equivalence Tests
Classification of Human Failure in Chemical Plants
| Highly cited | No |
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