Elastica: A compliant mechanics environment for soft robotic control

TL;DR

Elastica is an open-source simulation environment for soft robots that enables effective control development by accurately modeling complex continuum mechanics, demonstrated through reinforcement learning applications.

Contribution

We introduce Elastica, a computationally efficient, physically accurate simulation platform for soft, slender robots, facilitating advanced control strategies.

Findings

Successfully controlled a soft robotic arm using reinforcement learning

Elastica accurately models bending, twisting, shearing, and stretching behaviors

Enables development of control schemes for complex soft robots

Abstract

Soft robots are notoriously hard to control. This is partly due to the scarcity of models able to capture their complex continuum mechanics, resulting in a lack of control methodologies that take full advantage of body compliance. Currently available simulation methods are either too computational demanding or overly simplistic in their physical assumptions, leading to a paucity of available simulation resources for developing such control schemes. To address this, we introduce Elastica, a free, open-source simulation environment for soft, slender rods that can bend, twist, shear and stretch. We demonstrate how Elastica can be coupled with five state-of-the-art reinforcement learning algorithms to successfully control a soft, compliant robotic arm and complete increasingly challenging tasks.