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The GummiArm Project: A Replicable and Variable-Stiffness Robot Arm for Experiments on Embodied AI.

Martin F Stoelen^1,2,3, Ricardo de Azambuja⁴, Beatriz López Rodríguez¹

¹Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway.

Frontiers in Neurorobotics

|April 1, 2022

Summary

Researchers developed the GummiArm, an affordable, 3D-printable soft robot arm. This durable and easily repairable robotic arm enhances embodied AI research by enabling safe physical exploration and learning from failure.

Keywords:

3D printing embodied intelligence replicable robotics research soft robotics variable-stiffness actuators

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Area of Science:

Robotics
Artificial Intelligence
Embodied AI

Background:

Research robots for Embodied AI require physical exploration and learning from failure.
Existing robots are often too stiff, expensive, and fragile for safe, repeated experimentation.

Purpose of the Study:

To develop an open-source, affordable, and robust soft robot arm for Embodied AI research.
To enable easier replication of robotics experiments and concurrent design of AI 'brain' and 'body'.

Main Methods:

Designed a 6-year project resulting in the GummiArm, featuring human-inspired tendon actuation.
Incorporated variable-stiffness and damped actuation for safety and new research avenues.
Utilized hobby-grade 3D printing for arm structure and stretchable composite tendons for impact resistance.

Main Results:

The GummiArm is low-cost (<$6000), with easily replaceable 3D-printed parts (<$20 filament).
The arm exhibits dexterity for simple manipulation and is robust to impacts.
Demonstrated a repair cycle of minutes for damaged components.

Conclusions:

The GummiArm facilitates safer physical exploration and learning in Embodied AI research.
Its affordability, durability, and ease of replication promote productivity and reproducibility.
Enables concurrent development of robotic bodies and AI control systems.