Task-Specific Design Optimization and Fabrication for Inflated-Beam Soft Robots with Growable Discrete Joints

TL;DR

This paper introduces a design optimization method for inflatable soft robots with growable joints, aiming to achieve target reachability while minimizing joints and costs, enhancing safety and workspace.

Contribution

It presents a novel optimization framework for designing growable soft robots with discrete joints, considering material and actuation constraints, to improve reachability and efficiency.

Findings

Optimized robot designs reach all specified targets.

The approach reduces the number of joints needed.

The method effectively explores design trade-offs.

Abstract

Soft robot serial chain manipulators with the capability for growth, stiffness control, and discrete joints have the potential to approach the dexterity of traditional robot arms, while improving safety, lowering cost, and providing an increased workspace, with potential application in home environments. This paper presents an approach for design optimization of such robots to reach specified targets while minimizing the number of discrete joints and thus construction and actuation costs. We define a maximum number of allowable joints, as well as hardware constraints imposed by the materials and actuation available for soft growing robots, and we formulate and solve an optimization problem to output a planar robot design, i.e., the total number of potential joints and their locations along the robot body, which reaches all the desired targets, avoids known obstacles, and maximizes the workspace. We demonstrate a process to rapidly construct the resulting soft growing robot design. Finally, we use our algorithm to evaluate the ability of this design to reach new targets and demonstrate the algorithm's utility as a design tool to explore robot capabilities given various constraints and objectives.