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A multi-user multi-robot multi-goal multi-device human-robot interaction manipulation benchmark.

Akito Yoshida1, Rousslan Fernand Julien Dossa1, Marina Di Vincenzo1

  • 1Araya Inc., Tokyo, Japan.

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|October 13, 2025
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Summary
This summary is machine-generated.

A new benchmark, M4Bench, enables reproducible human-robot interaction (HRI) research. Standardized testing revealed that mouse/keyboard or gamepad controls outperform eye-tracker/EMG for manipulation tasks.

Keywords:
benchmarkhuman-robot interactionmulti-agentmultimodalshared autonomy

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Area of Science:

  • Robotics
  • Human-Computer Interaction
  • Cognitive Science

Background:

  • Reproducibility in human-robot interaction (HRI) research is limited by the absence of standardized benchmarks.
  • Current HRI platforms often lack flexibility for multi-user, multi-robot, and multi-device scenarios.

Purpose of the Study:

  • To introduce M4Bench, a flexible HRI platform for standardized, reproducible manipulation task research.
  • To enable quantitative comparisons of different user interfaces and input devices in HRI.

Main Methods:

  • Developed M4Bench, a multi-user, multi-robot, multi-goal, multi-device manipulation benchmark with a web-based interface.
  • Integrated support for various input devices including mouse, keyboard, gamepad, eye tracker, and EMG/EEG.
  • Implemented tracking of HRI metrics like task completion and command selection time.

Main Results:

  • A user study (n=50) compared five input devices and single-vs. multi-user control.
  • Performance was significantly worse with eye-tracker + EMG compared to mouse + keyboard or gamepad + gamepad (corrected p < 0.001).

Conclusions:

  • M4Bench provides a valuable tool for advancing reproducible HRI research.
  • Input device selection significantly impacts user performance in robotic manipulation tasks.