Stochastic models of compliant spine arrays for rough surface grasping

Abstract

This paper presents models of arrays of compliantly supported spines that attach to rough surfaces. The applications include climbing and perching robots. Surfaces are characterized in terms of asperity distributions, which lead to stochastic models of spine force capabilities over a range of loading directions. Models cover unidirectional spine arrays and pairs of opposed arrays that withstand normal forces pulling away from a surface. Experiments on a variety of surfaces confirm the predicted behavior. For opposed spine arrays, the overall load capability also depends on the preloading strategy for applying internal forces. Insights from the analysis guide the design of spine array mechanisms to allow, for example, a small aerial platform to attach to walls and ceilings.