A wearable haptic device for edge and surface simulation
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866918423505666048 |
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| author | Chen, Rui Mai, Xianlong Sanaei, Alireza Chiaradia, Domenico Frisoli, Antonio Leonardis, Daniele |
| author_facet | Chen, Rui Mai, Xianlong Sanaei, Alireza Chiaradia, Domenico Frisoli, Antonio Leonardis, Daniele |
| contents | Object manipulation is fundamental to virtual reality (VR) applications, yet conventional fingertip haptic devices fail to render certain tactile features relevant for immersive and precise interactions, as i.e. detection of edges. This paper presents a compact, lightweight fingertip haptic device (24.3 g) that delivers distinguishable surface and edge contact feedback through a novel dual-motor mechanism. Pressure distribution characterization using a 6 x 6 flexible sensor array demonstrates distinct contact patterns between the two stimulation modes. A preliminary user study with five participants achieved 93% average classification accuracy across four conditions (edge/surface contact with light/heavy pressure), with mean response times of 2.79 seconds. The results indicate that the proposed device can effectively convey edge and surface tactile cues, potentially enhancing object manipulation fidelity in VR environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_00752 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A wearable haptic device for edge and surface simulation Chen, Rui Mai, Xianlong Sanaei, Alireza Chiaradia, Domenico Frisoli, Antonio Leonardis, Daniele Robotics Human-Computer Interaction Object manipulation is fundamental to virtual reality (VR) applications, yet conventional fingertip haptic devices fail to render certain tactile features relevant for immersive and precise interactions, as i.e. detection of edges. This paper presents a compact, lightweight fingertip haptic device (24.3 g) that delivers distinguishable surface and edge contact feedback through a novel dual-motor mechanism. Pressure distribution characterization using a 6 x 6 flexible sensor array demonstrates distinct contact patterns between the two stimulation modes. A preliminary user study with five participants achieved 93% average classification accuracy across four conditions (edge/surface contact with light/heavy pressure), with mean response times of 2.79 seconds. The results indicate that the proposed device can effectively convey edge and surface tactile cues, potentially enhancing object manipulation fidelity in VR environments. |
| title | A wearable haptic device for edge and surface simulation |
| topic | Robotics Human-Computer Interaction |
| url | https://arxiv.org/abs/2604.00752 |