Soft Robotic Mannequin: Design and Algorithm for Deformation Control

TL;DR

This paper introduces a soft robotic mannequin system that uses pneumatic chambers and vision feedback to deform a soft membrane into various human body shapes, enabling realistic physical modeling.

Contribution

The paper presents a novel algorithm integrating vision feedback and optimization techniques for precise deformation control of a soft robotic mannequin.

Findings

Algorithm converges quickly with pose estimation inclusion.

Deformation accuracy verified through experiments.

Efficient derivative evaluation using Broyden updates.

Abstract

This paper presents a novel soft robotic system for a deformable mannequin that can be employed to physically realize the 3D geometry of different human bodies. The soft membrane on a mannequin is deformed by inflating several curved chambers using pneumatic actuation. Controlling the freeform surface of a soft membrane by adjusting the pneumatic actuation in different chambers is challenging as the membrane's shape is commonly determined by the interaction between all chambers. Using vision feedback provided by a structured-light based 3D scanner, we developed an efficient algorithm to compute the optimized actuation of all chambers which could drive the soft membrane to deform into the best approximation of different target shapes. Our algorithm converges quickly by including pose estimation in the loop of optimization. The time-consuming step of evaluating derivatives on the deformable membrane is avoided by using the Broyden update when possible. The effectiveness of our soft robotic mannequin with controlled deformation has been verified in experiments.