Frontiers in Virtual Reality (Feb 2023)

Effective haptic feedback type for robot-mediated material discrimination depending on target properties

  • Minami Takahashi,
  • Hikaru Nagano,
  • Yuichi Tazaki,
  • Yasuyoshi Yokokohji

DOI
https://doi.org/10.3389/frvir.2023.1070739
Journal volume & issue
Vol. 4

Abstract

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Haptic feedback enables material perception via remote robotics. Both force and vibration information are essential for haptic feedback, and it is important to understand their applicability in different situations. In this study, the relationship between the effective type of haptic feedback and target properties in robot-mediated material discrimination was investigated. A remote-control system including a force presentation device and a wearable vibrotactile display was constructed. In the first experiment, the discrimination performance of material hardness was compared between two types of feedback, force and hybrid (vibrotactile and force) conditions. The results show that both feedback systems allow statistically-significant discrimination of the stimuli, and a significant difference in correct-answer rates between the two feedback conditions was not observed. This indicates that the force system was effective for hardness discrimination, and that there was no superimposed effect of the hybrid system. In the second experiment, the discrimination performance of material roughness was compared between three types of feedback (force, vibrotactile, and hybrid). The results indicate that the rate of correct responses for hybrid feedback condition are significantly higher than those for the force condition. This suggests that hybrid feedback is effective for roughness discrimination. Therefore, the effective type of feedback depends on the properties of target materials, and the superimposed effect of hybrid feedback was only observed in roughness discrimination. These findings play an important role in selecting the best feedback method for a given situation or constructing multiple feedback methods that achieve high discrimination performance.

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