Will a sense of touch similar to that of humans ever be developed in robots? Results on the physics of friction for fingerprint-like ridges sliding across textured surfaces may lead the way to tactile robotic sensors.
When we rub a finger across a surface, our sense of touch is remarkably adept at distinguishing between different textures1. For example, astute clothes shoppers can easily feel the difference in texture between cotton and lower quality polyester fabrics, just as experienced cashiers can spot counterfeit banknotes from the feel of the paper. Writing in Physical Review Letters, Wandersman et al.2 provide a major advance towards understanding the physics behind these tactile sensations, showing how a modulated frictional signal is generated by fingerprint-like ridges rubbing against the roughness of an opposing surface. This improved understanding of the relationship between friction and surface textures should have an impact in many areas, but particularly in the field of tactile sensors for robotic design. Incorporating sensors capable of mimicking the human sense of touch has long been recognized3 as important for improving the ability of robots to grasp objects firmly without damaging them.
Wandersman et al.2 present measurements and analysis of the tangential or friction force generated as a rubbery elastomer block with periodic surface ridges slides over a rough glass surface. The ridges on the elastomer surface, which have periods ranging from 125 to 760 micrometres, serve as stand-ins for the epidermal ridges on human fingers (Fig. 1a). They show that, when pressed against the glass surface to form contact regions several millimetres in diameter, the elastomer deforms around the rough surface texture in the same way as the epidermal ridges would if pressed against such a surface.
With numerous ridges in contact, one might expect that any periodic variation in the friction force due to these ridges would average out; indeed, this can be shown analytically if the friction force generated in each microscopically small area in contact (much smaller than the width of a ridge) is strictly proportional to the local normal or loading force pressing the two surfaces into contact over this area. This linear relationship between the friction and load forces is usually referred to as Amontons' law of friction4, which states that the friction force, F, is proportional to the loading force, L, or F = μL, where μ is the coefficient of friction. However, the authors find that, rather than this friction modulation averaging to zero, the net friction acting on the elastomer block goes up and down slightly (by up to a few per cent) during the sliding experiments (Fig. 1b), with the same period as the ridges. And, surprisingly, the amplitude of this modulation actually increases when the net loading force increases.
One of the fundamental advances provided by Wandersman et al.2 is their analysis showing that, if the local friction coefficient depends even slightly on pressure (which is equivalent to friction being slightly non-linear with load), the modulation in friction can increase with loading force. They find good agreement between the experiments and a model in which friction varies non-linearly with load: F = ALγ, where γ = 0.87 ± 0.04 and A is a constant. In this model, the roughness of the surface against which the fingerprint-like ridges are being slid has the important role of providing a heterogeneous distribution of contact pressure locally along the ridges. As the roughness increases, a wider distribution of loading pressure occurs, leading to a larger modulation in friction as a result of the non-linear nature of friction with load. The spatial period of the ridges serves to concentrate the minute variation of friction caused by these texture-induced pressure modulations all at one frequency, making it much easier to discern this variation from the average net friction.
The sliding of fingerprint-like ridges over surfaces is not the only area in which Wandersman and colleagues' analysis should apply. Because friction forces are rarely strictly linear with loading forces (as postulated in Amontons' law)5, we believe that this analysis could provide a valuable way to use friction fluctuations to characterize surface roughness on many types of material pairs sliding against each other. The amplitude and the load-dependence of the fluctuations reveal information on the surface's topographic characteristics at length scales much smaller than that of the patterned ridges. As a result, we think that one exciting area to which the method developed by Wandersman et al.2 could be extended is the characterization of surface roughness down to the nanometre scale or even smaller atomic length scales.
For example, for many years, atomic-scale modulations of friction have been observed when the sharp tip of an atomic force microscope (AFM) slides across the periodic arrangement of atoms on a crystalline surface6. However, these AFM experiments typically require very small loading forces (nanonewtons) to maintain a contact area of only a few nanometres in diameter in order to see the atomic-scale modulation of friction. But, perhaps, with suitably designed patterned ridges and friction sensors, this ability to sense the atomic-level contribution to the friction modulation could be extended from the current nanometre-sized contact zones of AFMs to millimetre-sized contact zones, allowing future robotic fingers to feel the atomic-level contribution to surface texture.
About this article