Haptic Edge Detection Through Shear - Sorbonne Université Access content directly
Journal Articles Scientific Reports Year : 2016

Haptic Edge Detection Through Shear

Abstract

Most tactile sensors are based on the assumption that touch depends on measuring pressure. However, the pressure distribution at the surface of a tactile sensor cannot be acquired directly and must be inferred from the deformation field induced by the touched object in the sensor medium. Currently, there is no consensus as to which components of strain are most informative for tactile sensing. Here, we propose that shape-related tactile information is more suitably recovered from shear strain than normal strain. Based on a contact mechanics analysis, we demonstrate that the elastic behavior of a haptic probe provides a robust edge detection mechanism when shear strain is sensed. We used a jamming-based robot gripper as a tactile sensor to empirically validate that shear strain processing gives accurate edge information that is invariant to changes in pressure, as predicted by the contact mechanics study. This result has implications for the design of effective tactile sensors as well as for the understanding of the early somatosensory processing in mammals. A reliable mapping between the physical world and the acquired data is a basic issue faced by any artificial or natural sensory system. For instance, in vision, a fundamental challenge is to access robustly the geometry of a body from the structure of the captured light intensity, despite variations in the viewing conditions. This task is difficult because the intrinsic geometry of a body is not mapped one-to-one to the geometry of images
Fichier principal
Vignette du fichier
srep23551.pdf (1.29 Mo) Télécharger le fichier
Origin : Publication funded by an institution
Loading...

Dates and versions

hal-01296656 , version 1 (01-04-2016)

Licence

Attribution

Identifiers

Cite

Jonathan Platkiewicz, Hod Lipson, Vincent Hayward. Haptic Edge Detection Through Shear. Scientific Reports, 2016, 6, pp.23551. ⟨10.1038/srep23551⟩. ⟨hal-01296656⟩
100 View
142 Download

Altmetric

Share

Gmail Facebook X LinkedIn More