Soap-bubble Optimization of Gaits
This work addresses gait optimization for robotic or biological locomoting systems, presenting a novel method that is incremental in its application to known problems.
The paper tackled the problem of optimizing gaits for kinematic locomoting systems by developing a geometric variational algorithm inspired by soap bubble physics, and demonstrated it on various geometries like Purcell's swimmer to maximize displacement and efficiency in translation and turning motions.
In this paper, we present a geometric variational algorithm for optimizing the gaits of kinematic locomoting systems. The dynamics of this algorithm are analogous to the physics of a soap bubble, with the system's Lie bracket supplying an "inflation pressure" that is balanced by a "surface tension" term derived from a Riemannian metric on the system's shape space. We demonstrate this optimizer on a variety of system geometries (including Purcell's swimmer) and for optimization criteria that include maximizing displacement and efficiency of motion for both translation and turning motions.