Bioinspired Ciliary Force Sensor for Robotic Platforms

Ribeiro, Pedro; Khan, M. A.; Alfadhel, Ahmed; Kosel, Jürgen; Franco, Fernando; Cardoso, Susana; Bernardino, Alexandre; Schmitz, Alexander; Santos-Victor, José; Jamone, Lorenzo

doi:10.1109/lra.2017.2656249

Cited by 42 publications

(27 citation statements)

References 26 publications

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“…Cilia (from the Latin cilium, “eyelash”) are thin, hair‐like structures that cover the inner layer of mammalian trachea for mucus transportation out of the lungs [ 1 ] and cover the outer surface of micro‐organisms (e.g., paramecium) to aid in locomotion, food capture, tactile sensing, and mating reactions. [ 2 ] Numerous studies have focused on replicating these morphologies and exploring artificial cilia for applications in microfluidic propulsion/mixing, [ 3–7 ] surface property modification, [ 8 ] enhancing catalytic reactions, [ 9,10 ] sensing, [ 11–14 ] microrobots/swimmers, [ 15,16 ] object transportation, [ 17–19 ] and cell stimulation. [ 20 ]…”

Section: Figurementioning

confidence: 99%

Optomechanically Actuated Microcilia for Locally Reconfigurable Surfaces

Kim

Guidetti

et al. 2020

Advanced Materials

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torque that result in large material deformation. The spatial distribution of magnetic fields makes it challenging to obtain spatially selective actuation. Previous reports have shown localized control of cilia by controlling multiple permanent magnets independently [23] or by fabricating materials with embedded magnetic domains with different magnetization directions. [24,25] However, remote and precise local actuation remains challenging for magnetic microcilia structures. Light, by contrast, propagates long distances, wirelessly, without dramatic distortion, and, more importantly, using light allows for local stimulation with both high spatial and high temporal resolution. In

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Section: Figurementioning

confidence: 99%

Optomechanically Actuated Microcilia for Locally Reconfigurable Surfaces

Kim

Guidetti

et al. 2020

Advanced Materials

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“…With the development of microsystem technology, artificial cilia can now be fabricated and are foreseen to find applications in microrobotic devices, such as microswimmers, microsensors, micropumps, and micromixers . The vast majority of artificial cilia consist of microactuators that are incorporated in silicone rubber pillars or plate‐like flexible structures in order to mimic the biological hair‐like design.…”

Section: Introductionmentioning

confidence: 99%

Artificial Soft Cilia with Asymmetric Beating Patterns for Biomimetic Low‐Reynolds‐Number Fluid Propulsion

Milana

Gorissen

Peerlinck

et al. 2019

Adv Funct Materials

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In nature, liquid propulsion in low-Reynolds-number regimes is often achieved by arrays of beating cilia with various forms of motion asymmetry. In particular, spatial asymmetry, where the cilia follow a different trajectory in their effective and recovery strokes, is an efficient way of generating flow in low Reynolds regimes. However, this type of asymmetry is difficult to mimic and control artificially. In this paper, an artificial soft cilium that comprises two pneumatic actuators that can be controlled individually is developed. These two independent degrees of freedom allow for the first time adjustment and study of spatial asymmetry in the cilium's beating pattern. Using low-Reynolds-number flow measurements, it is confirmed that spatial asymmetry allows for the generation of fluid propulsion. These twodegree-of-freedom soft cilia provide a platform to study ciliary fluid transport mechanisms and to mimic biologic viscous propulsion.The ORCID identification number(s) for the author(s) of this article can be found under https://doi.org/10.1002/adfm.201900462. of a single cilium as well as for whole cilia arrays. For a single cilium, orientational, temporal, and spatial asymmetry can be distinguished, [6] where the latter has the highest impact on low Reynolds fluid propulsion. Spatial asymmetry, where the cilium tip describes a different path during the effective and recovery stroke, is quantified by the swept area; the larger the area, the higher the net flow. [7] At the array level, an additional type of asymmetry has been observed, metachronal asymmetry, which is characterized by a phase difference between neighboring cilia [8] that gives rise to a global wave-like movement.With the development of microsystem technology, artificial cilia can now be fabricated and are foreseen to find applications in microrobotic devices, such as microswimmers, [9,10] microsensors, [11] micropumps, [12][13][14] and micromixers. [15][16][17][18] The vast majority of artificial cilia consist of microactuators that are incorporated in silicone rubber pillars or plate-like flexible structures in order to mimic the biological hair-like design. Current actuation methods include electric fields, [15] magnetic fields, [19][20][21][22][23] vibrations, [24,25] mechanical forces, [26] or pressurized fluids. [27,28] However, asymmetric motion remains the most challenging feature to mimic in artificial cilia systems. In nature, nonreciprocal beating is achieved by a change in bending stiffness between the effective and recovery stroke: [29] A higher stiffness is observed during the fast effective stroke, where the cilium does not deform significantly, whereas in the slower recovery phase the cilium has a lower stiffness and tends to be deformed by the drag forces. To mimic such an asymmetric motion, the artificial cilium needs at least two deformation modes that need to be sequentially addressed. This can be achieved through elastic instabilities, [7] the interaction between elastic, viscous, and actuation forces, [26,30] or a multise...

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“…Based on a variety of transduction principles, such as piezoresistive [7], capacitive [8], piezoelectric [9], electromagnetic [10], and optoelectronic principles [11], etc., researchers have developed different types of tactile sensors capable of detecting one or more kinds of tactile information such as contact position, force, relative sliding, temperature, and roughness. Normally, the parts of the tactile sensor can be divided into those of array structure and the non-array structure.…”

Section: Introductionmentioning

confidence: 99%

A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network

You-zhi

Lin

et al. 2018

Sensors

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Electronic skin is an important means through which robots can obtain external information. A novel flexible tactile sensor capable of simultaneously detecting the contact position and force was proposed in this paper. The tactile sensor had a three-layer structure. The upper layer was a specially designed conductive film based on indium-tin oxide polyethylene terephthalate (ITO-PET), which could be used for detecting contact position. The intermediate layer was a piezoresistive film used as the force-sensitive element. The lower layer was made of fully conductive material such as aluminum foil and was used only for signal output. In order to solve the inconsistencies and nonlinearity of the piezoresistive properties for large areas, a Radial Basis Function (RBF) neural network was used. This includes input, hidden, and output layers. The input layer has three nodes representing position coordinates, X, Y, and resistor, R. The output layer has one node representing force, F. A sensor sample was fabricated and experiments of contact position and force detection were performed on the sample. The results showed that the principal function of the tactile sensor was feasible. The sensor sample exhibited good consistency and linearity. The tactile sensor has only five lead wires and can provide the information support necessary for safe human—computer interactions.

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Bioinspired Ciliary Force Sensor for Robotic Platforms

Cited by 42 publications

References 26 publications

Optomechanically Actuated Microcilia for Locally Reconfigurable Surfaces

Optomechanically Actuated Microcilia for Locally Reconfigurable Surfaces

Artificial Soft Cilia with Asymmetric Beating Patterns for Biomimetic Low‐Reynolds‐Number Fluid Propulsion

A Piezoresistive Tactile Sensor for a Large Area Employing Neural Network

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