MEVITA: Open-Source Bipedal Robot Assembled from E-Commerce Components via Sheet Metal Welding

TL;DR

MEVITA is an open-source, easily assembled bipedal robot built from e-commerce components, utilizing sheet metal welding to simplify construction and employing reinforcement learning for robust walking behaviors.

Contribution

The paper introduces MEVITA, a scalable, easy-to-assemble bipedal robot made from readily available parts, advancing open-source robotics with simplified design and effective simulation transfer.

Findings

Successful simulation and real-world walking behaviors

Reduced component count through sheet metal welding

Open-source hardware and software available for community use

Abstract

Various bipedal robots have been developed to date, and in recent years, there has been a growing trend toward releasing these robots as open-source platforms. This shift is fostering an environment in which anyone can freely develop bipedal robots and share their knowledge, rather than relying solely on commercial products. However, most existing open-source bipedal robots are designed to be fabricated using 3D printers, which limits their scalability in size and often results in fragile structures. On the other hand, some metal-based bipedal robots have been developed, but they typically involve a large number of components, making assembly difficult, and in some cases, the parts themselves are not readily available through e-commerce platforms. To address these issues, we developed MEVITA, an open-source bipedal robot that can be built entirely from components available via e-commerce. Aiming for the minimal viable configuration for a bipedal robot, we utilized sheet metal welding to integrate complex geometries into single parts, thereby significantly reducing the number of components and enabling easy assembly for anyone. Through reinforcement learning in simulation and Sim-to-Real transfer, we demonstrated robust walking behaviors across various environments, confirming the effectiveness of our approach. All hardware, software, and training environments can be obtained from https://github.com/haraduka/mevita .