An audiovisual assistance system for beam-stopper positioning in intraoperative electron radiotherapy: experimental evaluation under manual and teleoperated operation

Introduction Robotic positioning tasks involving indirectly observable targets present significant spatial reasoning challenges in human–robot interaction (HRI). A clinically relevant example is beam stopper positioning during intraoperative electron radiotherapy (IOERT), which requires aligning a mobile shielding device with an unseen radiation beam axis. Methods We propose an audiovisual assistance system that estimates the real-time intersection between the radiation beam and the floor plane, providing multimodal spatial guidance during both manual and teleoperated control. A within-subject experimental study was conducted to evaluate positioning accuracy, execution time, user experience, and workload across assisted and unassisted conditions. Results Audiovisual guidance reduced the mean positioning error by approximately 80% (from ∼ 0.30 m to less than 0.07 m) across both control modes without increasing completion time. Furthermore, the system mitigated performance degradation caused by unfavorable workspace geometries, minimized skill-based differences between operators, and significantly lowered perceived mental workload. Discussion These findings demonstrate that real-time multimodal feedback is a robust, effective strategy for improving spatial accuracy, consistency, and usability in HRI tasks with obscured target geometries.

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Journal
Frontiers in Robotics and AI
Published
2026-10-30
DOI
https://doi.org/10.3389/frobt.2026.1955069
Primary Topic
Teleoperation and Haptic Systems
Type
article
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article

An audiovisual assistance system for beam-stopper positioning in intraoperative electron radiotherapy: experimental evaluation under manual and teleoperated operation

Irene del Canto, Silvia Casans Berga, Vicent Girbés-Juan, E. Sanchís et al.
2 links
Frontiers in Robotics and AI
Teleoperation and Haptic Systems
article

An audiovisual assistance system for beam-stopper positioning in intraoperative electron radiotherapy: experimental evaluation under manual and teleoperated operation

Irene del Canto, Silvia Casans Berga, Vicent Girbés-Juan, E. Sanchís, Laura Garrido-Rey, José Manuel Deltoro
article en

Abstract

Introduction Robotic positioning tasks involving indirectly observable targets present significant spatial reasoning challenges in human–robot interaction (HRI). A clinically relevant example is beam stopper positioning during intraoperative electron radiotherapy (IOERT), which requires aligning a mobile shielding device with an unseen radiation beam axis. Methods We propose an audiovisual assistance system that estimates the real-time intersection between the radiation beam and the floor plane, providing multimodal spatial guidance during both manual and teleoperated control. A within-subject experimental study was conducted to evaluate positioning accuracy, execution time, user experience, and workload across assisted and unassisted conditions. Results Audiovisual guidance reduced the mean positioning error by approximately 80% (from ∼ 0.30 m to less than 0.07 m) across both control modes without increasing completion time. Furthermore, the system mitigated performance degradation caused by unfavorable workspace geometries, minimized skill-based differences between operators, and significantly lowered perceived mental workload. Discussion These findings demonstrate that real-time multimodal feedback is a robust, effective strategy for improving spatial accuracy, consistency, and usability in HRI tasks with obscured target geometries.

Frontiers in Robotics and AIVol. 13
Universitat de València (ES), Instituto de Física Corpuscular (ES)
Good health and well-being
Openalex Percentile: Top 23%
Teleoperation and Haptic Systems
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An audiovisual assistance system for beam-stopper positioning in intraoperative electron radiotherapy: experimental evaluation under manual and teleoperated operation — Irene del Canto, Silvia Casans Berga, et al. · Frontiers in Robotics and AI (2026) | TGRS Research Map | TGRS