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Multimodal haptic perception is essential for enhancing perceptual experiences in augmented reality applications. To date, several artificial tactile interfaces have been developed to perceive pressure and precontact signals, while simultaneously detecting object type and softness with quantified modulus still remains challenging. Here, inspired by the campaniform sensilla on insect antennae, we proposed a hemispherical bimodal intelligent tactile sensor (BITS) array using the triboelectric effect. The system is capable of softness identification, modulus quantification, and material type recognition. In principle, due to the varied deformability of materials, the BITS generates unique triboelectric output fingerprints when in contact with the tested object. Furthermore, owing to the different electron affinities, the BITS array can accurately recognize material type (99.4% accuracy), facilitating softness recognition (100% accuracy) and modulus quantification. It is promising that the BITS based on the triboelectric effect has the potential to be miniaturized to provide real-time accurate haptic information as an artificial antenna toward applications of human-machine integration. [ABSTRACT FROM AUTHOR]

The article offers information on introducing damage intelligent soft-bodied systems via a network of self-healing light guides for dynamic sensing (SHeaLDS). It discusses that With optimized material and structural design for hyperelastic deformation of the robot and autonomous self-healing capacity, SHeaLDS provides reliable dynamic sensing at large strains with no drift or hysteresis, is resistant to punctures, and self-heals from cuts at room temperature with no external intervention.

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The article discusses a study on sensing module that converts physical or chemical stimuli into electrical signals. It mentions that a combination of flipped silicon nanomembrane phototransistors and stimuli-responsive materials presents low-power consumption and demonstrates great functional expansibility of sensing targets.