Guest Editorial Special Issue on Biorobotics

Dario, P.; Hannaford, Blake; Takanishi, A.

doi:10.1109/tro.2008.918929

Cited by 10 publications

(4 citation statements)

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“…This comparative approach is fundamental to define design parameters in developing bioinspired sensory systems but it could be also useful to provide hints and suggestions to develop experimental protocols and models in neurophysiology. BioRobotics offers the possibility to develop emulator of the human subjects [ 1 ], with different characteristics and design parameters, as in the work presented in this paper we selectively modify a specific parameter (the curvature of fingerprints) to evaluate the related effect. In order to support the significance of the artificial touch results, in parallel we present a selection of electrophysiological studies by means of microneurographic recordings of the activity of single, identified afferent units in the fingertips of healthy human volunteers [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Roughness Encoding in Human and Biomimetic Artificial Touch: Spatiotemporal Frequency Modulation and Structural Anisotropy of Fingerprints

Oddo

Beccai

Wessberg

et al. 2011

Sensors

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The influence of fingerprints and their curvature in tactile sensing performance is investigated by comparative analysis of different design parameters in a biomimetic artificial fingertip, having straight or curved fingerprints. The strength in the encoding of the principal spatial period of ridged tactile stimuli (gratings) is evaluated by indenting and sliding the surfaces at controlled normal contact force and tangential sliding velocity, as a function of fingertip rotation along the indentation axis. Curved fingerprints guaranteed higher directional isotropy than straight fingerprints in the encoding of the principal frequency resulting from the ratio between the sliding velocity and the spatial periodicity of the grating. In parallel, human microneurography experiments were performed and a selection of results is included in this work in order to support the significance of the biorobotic study with the artificial tactile system.

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Section: Introductionmentioning

confidence: 99%

Roughness Encoding in Human and Biomimetic Artificial Touch: Spatiotemporal Frequency Modulation and Structural Anisotropy of Fingerprints

Oddo

Beccai

Wessberg

et al. 2011

Sensors

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“…In all these application domains, the artificial tactile sensing system should cope with three main challenges [106]: development of effective and usable robotic and mechatronic systems;increased understanding of mechanisms implemented by different biological systems;effective interactions with biological systems.…”

Section: Discussion Application Domains and Conclusionmentioning

confidence: 99%

Synthetic and Bio-Artificial Tactile Sensing: A Review

Lucarotti

Oddo

Vitiello

et al. 2013

Sensors

133

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This paper reviews the state of the art of artificial tactile sensing, with a particular focus on bio-hybrid and fully-biological approaches. To this aim, the study of physiology of the human sense of touch and of the coding mechanisms of tactile information is a significant starting point, which is briefly explored in this review. Then, the progress towards the development of an artificial sense of touch are investigated. Artificial tactile sensing is analysed with respect to the possible approaches to fabricate the outer interface layer: synthetic skin versus bio-artificial skin. With particular respect to the synthetic skin approach, a brief overview is provided on various technologies and transduction principles that can be integrated beneath the skin layer. Then, the main focus moves to approaches characterized by the use of bio-artificial skin as an outer layer of the artificial sensory system. Within this design solution for the skin, bio-hybrid and fully-biological tactile sensing systems are thoroughly presented: while significant results have been reported for the development of tissue engineered skins, the development of mechanotransduction units and their integration is a recent trend that is still lagging behind, therefore requiring research efforts and investments. In the last part of the paper, application domains and perspectives of the reviewed tactile sensing technologies are discussed.

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“…Biorobotics fosters the convergence of technological achievements with new scientific knowledge and helps us understand the underlying natural phenomena and behaviors (Dario et al, 2008). This approach has often been depicted in the light of bioinspiration and biomimetics, and it gives rise to morphological computation, a novel paradigm asserting the role of materials in taking over some of the processes normally attributed to control (Pfeifer et al, 2007;Laschi and Cianchetti, 2014), in conjunction with neuromorphic engineering in case of mimicry of neural mechanisms and architectures (Spigler et al, 2012).…”

Section: Biomimetic Artificial Touchmentioning

confidence: 99%

Biomimetic tactile sensing

Dahiya¹,

Oddo²,

Mazzoni³

et al. 2015

Biomimetic Technologies

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What would happen if we had all sense modalities but the "touch?" A simple experiment of manipulating objects after putting hands on an ice block for a moment can probably provide an answer to this question. In one such experiment, the skin on a volunteer's hand was anesthetized so that tactile information from mechanoreceptors-the specialized nerve endings that respond to mechanical stimulation-was no longer available to the brain (Westling and Johannson, 1984). It was observed that even though volunteers could see what they were doing, they could no longer maintain a stable grasp of the objects. This indicates that the movements become inaccurate and unstable in the absence of "sense of touch." The difficulties that humans could face in the absence of sense of touch also point toward the importance of touch sense modality in robots, especially when they are expected to work in a human environment.The touch sensing allows us to assess the size, shape, softness, and texture of objects. It helps us understand the interaction behaviors of the real world objects-which depend on their weight; stiffness; on how their surface feels when touched; how they deform on contact; and how they move when pushed. In applications such as robotics, tactile information is useful in a number of ways. In manipulative tasks, the tactile data are used as a control parameter and the tactile information typically includes contact point estimation, surface normal and curvature measurement, and slip detection (Fearing, 1990;Howe, 1994). A measure of the contact forces (both magnitude and direction) allows the grasp force control-needed to maintain stable grasps. In a real world interaction that involves, both, manipulative and exploratory tasks, the tactile information such as hardness/softness (Shikida et al., 2003), temperature, and vibrations are needed to understand diverse properties of the contacted objects.The need for suitable tactile sensing system in robotics has resulted in a large number of touch sensors and tactile sensing arrays by exploring nearly all modes of transduction, viz., resistive, capacitive, piezoelectric, magnetic, quantum tunneling, etc. (Dahiya et al., 2010b;Lee and Nicholls, 1999;Dahiya and Valle, 2013). Currently, many research groups are also working toward developing skin-like artificial systems for large area tactile sensing. However, the touch sensor technology developed so far is largely insufficient for robotics, even if there is significant success in other areas such as mobile telephony. This could be attributed to a number of factors such as availability of less than satisfactory sensory skins, insufficient methods of processing tactile data, the lack of systems approach, and the lack of mechanical flexibility and robust sensory structures. Often, tactile data are processed with techniques adapted from visual data processing, which may not be a correct approach as the touch sensing is distributed over a much broader area than vision. As a Biomimetic Technologies. http://dx.

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Guest Editorial Special Issue on Biorobotics

Cited by 10 publications

References 0 publications

Roughness Encoding in Human and Biomimetic Artificial Touch: Spatiotemporal Frequency Modulation and Structural Anisotropy of Fingerprints

Roughness Encoding in Human and Biomimetic Artificial Touch: Spatiotemporal Frequency Modulation and Structural Anisotropy of Fingerprints

Synthetic and Bio-Artificial Tactile Sensing: A Review

Biomimetic tactile sensing

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