Influence of Autonomy and Interfaces on Human and Multi-Robot Teams
A Study on Planetary Exploration
Bibliographic Data
| ID | 22190701 |
|---|---|
| Authors | Marcel Kaufmann (0000-0001-5132-592X, Polytechnique Montréal), Giovanni Beltrame (0000-0001-9755-8630, Polytechnique Montréal) |
| Year | 2026 |
| Publication date | 2026-06-29 |
| Peer Reviewed | Yes |
| Open Access | No |
| 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 | 10.1145/3822499 |
| OpenAlex | W7166534764 |
| Language | EN |
| References cited | 34 |
Advances in robotic autonomy and interfaces have transformed human-robot teaming across domains, from disaster response to planetary science. However, critical gaps remain in understanding how autonomy and interface design affect human performance and cognitive demands, especially in large-scale, unstructured environments such as those on the Moon or Mars. We present a human-in-the-loop system comprising two (semi-)autonomous robots supervised by a single human operator. The system was evaluated in real caves at Lava Beds National Monument (California) and in a controlled within-subject study (n=38) at Polytechnique Montréal exploring both real and simulated caves. Participants interacted using either a traditional screen interface or a novel real-time, immersive VR interface, developed for this study and field-tested during NASA's BRAILLE campaign. We find that continuous physiological measurements (HRV) align with subjective NASA TLX scores in the context of human and multi-robot planetary exploration. Compared to benchmarks from prior studies, the screen interface resulted in low workload, while VR was rated in the low-to-moderate range. The low-autonomy VR-waypoint condition resulted in the least effective performance, with the fewest automated science detections, whereas both the full-autonomy VR and screen-based conditions yielded comparably higher exploration and detection performance. Both interfaces supported high situational awareness, with accuracy measures near 90%. Autonomy did not significantly affect situational awareness, but full-autonomy did reduce operator input effort. Trust levels did not significantly vary across conditions, motivating more detailed assessment methods in future studies. The results inform how to align interface design and autonomy to support effective multi-robot supervision in future missions
Affordance · Autonomy · Human–robot interaction · Situation awareness · Usability · User interface · Healthcare Technology and Patient Monitoring · Human-Automation Interaction and Safety · Social Robot Interaction and HRI
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| Citation velocity | historical |
|---|---|
| Highly cited | No |