Bionic Compound Eye-Inspired High Spatial and Sensitive Tactile Sensor

Song, Lixin; Zhu, Huan; Zheng, Yelong; Zhao, Meirong; Tee, Clarence Augustine Th

doi:10.1109/tim.2021.3063757

Cited by 24 publications

(10 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[43] Fang et al proposed a high-density array of curved 3D tactile sensors inspired by the compound eye. [44] It can ensure uniform reception of contact force information at all azimuthal angles (0.000280 mN Gray −1 for normal force and 0.0262 N µm −1 for shear force) and convert curved images to flat images using lossless light cones.…”

Section: Sensorsmentioning

confidence: 99%

Multifunctional Biomimetic Microstructured Surfaces for Healthcare Applications

Jia

Jiang

Zhang

et al. 2022

Adv Materials Inter

View full text Add to dashboard Cite

The wings of butterflies and birds prevent wetting by rain and maintain the capability of flight. Water rolls in droplets on the surface of lotus leaves without collapsing to wet the whole surface, leading to the discovery of superhydrophobicity. The superhydrophobicity originates from the synergistic effect of the hierarchical microarray structure of the lotus leaf surface and low surface energy substances. The superhydrophobic surfaces have been applied in the fields of self-cleaning surfaces, [8] liquid transportation, [9] and antifouling surfaces. [10] The

show abstract

Section: Sensorsmentioning

confidence: 99%

Multifunctional Biomimetic Microstructured Surfaces for Healthcare Applications

Jia

Jiang

Zhang

et al. 2022

Adv Materials Inter

View full text Add to dashboard Cite

show abstract

“…In fact, the earliest vision-based tactile sensors were based on the optical waveguide . According to the principle of optical waveguide, we have proposed a novel high-density arrayed and curved 3D tactile sensor based on bionic compound eye, which realized the high sensitivity 3D tactile force measurement . In this study, we proposed a vision-based contact adhesion measurement (VisCAM) method to convert the physical contact adhesion to the optical signal, and the adhesion force was transformed into a 2D image to be able to send feedback of the adhesion information on the soft matter.…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Contact Adhesion Measurement Method on Soft Matter Surfaces

Zhu

et al. 2023

Langmuir

Self Cite

View full text Add to dashboard Cite

Adhesion property measurements contribute to a comprehensive understanding of the mechanical properties of soft matters. Indentation tests are a common method for measuring the adhesion force. However, indenters generally have a large volume and a small sensing angle and, thus, are not conducive to local detection in high-precision environments. Here, we propose a vision-based contact adhesion measurement (VisCAM) method to achieve the contact image and adhesion force on soft matter surfaces from the perspective of indentation direction. The coupling of the 7.6 mm diameter probe and a flexible fiber makes the system similar to a miniaturized endoscope. Classical contact theories and finite element models are used for the contact mechanics analysis of silicone rubber. The image grayscale–load mathematical model is constructed based on the change in contact light spot. Finally, the uncertainty of the system is less than 4%, and the measurement error is 0.04 N. In-vitro kidney indentation experiments showed that the local adhesion force measurement of soft tissues can be completed. Our method provides better solutions for understanding the adhesion properties of soft matters.

show abstract

“…Recent advances in electronics and microelectromechanical system (MEMS) manufacturing have allowed the sophistication of sensors and robotic devices to grow by leaps and bounds [1]- [3]. Robotic hands and prosthetic devices provide robots with humans' ability to interact with the surroundings and restore lost abilities for amputees [3]- [6]. The preeminent modality of choice for robotic devices that need to interact with the environment is vision [7]- [9].…”

Section: Introductionmentioning

confidence: 99%

“…State-of-the-art sensor solutions, from academia and industry, are typically hard to manufacture, expensive, and lacking in temporal as well as spatial resolution [17]- [19]. The majority of the solutions mainly focus on replicating the fingers tips [3], [10], [20], [21] or have sensors covering only a limited part of the hand palm [1]- [3], [22]- [24]. While [25] presents a system with full hand coverage, they use a small number of sensing elements (i.e., 16) and therefore only prove the functionality of the system with seven objects.…”

Section: Introductionmentioning

confidence: 99%