A tuned mass amplifier for enhanced haptic feedback. (September 2021)

• Record Type: Journal Article
• Authors: Injeti, Sai Sharan; Israr, Ali; Liu, Tianshu; Mengüç, Yiğit; Piazza, Daniele; Shin, Dongsuk D.
• Is Part Of: Mechanics of materials. Volume 160(2021)
• Publication Date: 2021-09
• Subjects: Vibration -- Haptics -- Optimal design -- Deep learning -- 3-D printing; Strength of materials -- Periodicals; Mechanics, Applied -- Periodicals; Résistance des matériaux -- Périodiques; Mécanique appliquée -- Périodiques; Mechanics, Applied; Strength of materials; Periodicals; Electronic journals; 620.11
• DOI: 10.1016/j.mechmat.2021.103979
• Languages: English
• ISSNs: 0167-6636

Abstract

Abstract: Vibro-tactile feedback is, by far the most common haptic interface in wearable or touchable devices. This feedback can be amplified by controlling the wave propagation characteristics in devices, by utilizing phenomena such as structural resonance. However, much of the work in vibro-tactile haptics has focused on amplifying local displacements in a structure by increasing local compliance. In this paper, we show that engineering the resonance mode shape of a structure with embedded localized mass amplifies the displacements without compromising on the stiffness or resonance frequency. The resulting structure, i.e., a tuned mass amplifier, produces higher tactile forces (7.7 times) compared to its counterpart without a mass, while maintaining a low frequency. We optimize the proposed design using a combination of a neural network and sensitivity analysis, and validate the results with experiments on 3-D printed structures. We also study the performance of the device on contact with a soft material, to evaluate the interaction with skin. Potential avenues for future work are also presented, including small form factor wearable haptic devices and remote haptics. Highlights: We present a method to decouple stiffness, displacements, and frequency of resonance. We design for high haptics forces at resonance, at low frequency. We couple resonance between a primary and secondary structure with an embedded mass. We show an optimization method that uses a sensitivity analysis and a neural network. We demonstrate the device with experiments on 3-D printed samples.