HumanoidTurk: Expanding VR Haptics with Humanoids for Driving Simulations

要旨

We explore how humanoid robots can be repurposed as haptic media, extending beyond their conventional role as social, assistive, collaborative agents. To illustrate this approach, we implemented HumanoidTurk, taking a first step toward a humanoid-based haptic system that translates in-game g-force signals into synchronized motion feedback in VR driving. A pilot study involving six participants compared two synthesis methods, leading us to adopt a filter-based approach for smoother and more realistic feedback. A subsequent study with sixteen participants evaluated four conditions: no-feedback, controller, humanoid+controller, and human+controller. Results showed that humanoid feedback enhanced immersion, realism, and enjoyment, while introducing moderate costs in terms of comfort and simulation sickness. Interviews further highlighted the robot’s consistency and predictability in contrast to the adaptability of human feedback. From these findings, we identify fidelity, adaptability, and versatility as emerging themes, positioning humanoids as a distinct haptic modality for immersive VR.

著者
DaeHo Lee
Gwangju Institute of Science and Technology, Gwangju, Korea, Republic of
Ryo Suzuki
University of Colorado Boulder, Boulder, Colorado, United States
Jin-Hyuk Hong
Gwangju Institute of Science and Technology, Gwangju, Korea, Republic of

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Reflecting on Haptics

P1 - Room 113
7 件の発表
2026-04-16 20:15:00
2026-04-16 21:45:00