A Holistic Evaluation of Teleoperation Interfaces for Robotic Manipulation
Bibliographic Data
| ID | 22190820 |
|---|---|
| Authors | Shaid Hasan (0000-0002-0076-5287, University of Virginia), Mohammad Samin Yasar (0000-0002-4684-2823, University of Virginia), Tariq Iqbal (0000-0003-0133-1234, University of Virginia) |
| Year | 2026 |
| Volume | 15 |
| Issue | 2 |
| Pages | 1-42 |
| Publication date | 2026-03-31 |
| 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 | 10.1145/3785141 |
| OpenAlex | W7115167413 |
| Language | EN |
| References cited | 89 |
Robot teleoperation has become increasingly crucial for extending human capabilities in inaccessible or hazardous environments and facilitating human–robot collaboration. While significant advancements have been made in teleoperation interfaces, the success of these systems critically depends on how effectively humans can interact with and control robotic systems across diverse manipulation tasks. However, existing research primarily evaluates interfaces within specific tasks or applications, lacking systematic assessment across different manipulation scenarios. This limitation leads to suboptimal interface selection that can compromise task efficiency in critical domains and impede the collection of high-quality demonstrations for robot learning. To address these gaps, we first introduce a novel two-axis Robotic Manipulation Task Taxonomy that systematically categorizes manipulation tasks based on their fundamental control requirements: Motion Type (translation-dominant vs. rotation-dominant) and Engagement Type (rigid vs. non-rigid object interactions). We conducted a comprehensive user study ( \(n=30\) ) evaluating three distinct teleoperation interfaces (Gamepad, 3D Mouse, and Virtual Reality (VR) Controller) based on this taxonomy. Our results indicate that the Gamepad and 3D mouse significantly outperformed the VR Controller in task completion time across all task categories. In contrast, the VR Controller showed higher first-attempt success rates but caused significantly greater cognitive load across all NASA Task Load Index (NASA-TLX) subscales compared to the Gamepad interface, and specifically higher mental demand, physical demand, and effort compared to the 3D mouse. Our results also indicate that although prior familiarity with an interface lowered perceived workload and enhanced perceived performance, it did not translate into improvements in actual task success rates or completion times. These insights provide valuable guidelines for optimizing teleoperation interfaces based on task requirements and highlight the importance of considering both cognitive demands and user experience in interface design
Cognitive Load · Robot · Teleoperation · Telerobotics · Virtual reality · Workload · Human-Automation Interaction and Safety · Teleoperation and Haptic Systems · Virtual Reality Applications and Impacts
Cognitive Load Theory
Reliability and Inter-rater Reliability in Qualitative Research
Thematic analysis
Intuitive, Efficient and Ergonomic Tele-Nursing Robot Interfaces
Design and Evaluation of an Augmented Reality Head-mounted Display Interface for Human Robot Teams Collaborating in Physically Shared Manufacturing Tasks
Imprint
Acquisition of cognitive skill
Beyond Usability Evaluation
| Citation velocity | historical |
|---|---|
| Highly cited | No |