MEVIUS: A Quadruped Robot Easily Constructed through E-Commerce with Sheet Metal Welding and Machining

TL;DR

This paper introduces MEVIUS, a durable, easily assembled quadruped robot made from sheet metal and off-the-shelf parts, designed for DIY construction via e-commerce, capable of outdoor terrain traversal using reinforcement learning.

Contribution

The study presents a novel metal quadruped robot that is simple to construct through e-commerce, emphasizing durability, minimal components, and ease of maintenance, with demonstrated outdoor capabilities.

Findings

Successfully built and assembled MEVIUS using only e-commerce parts.

Demonstrated MEVIUS's ability to traverse rough terrains.

Validated the robot's durability and outdoor performance.

Abstract

Quadruped robots that individual researchers can build by themselves are crucial for expanding the scope of research due to their high scalability and customizability. These robots must be easily ordered and assembled through e-commerce or DIY methods, have a low number of components for easy maintenance, and possess durability to withstand experiments in diverse environments. Various quadruped robots have been developed so far, but most robots that can be built by research institutions are relatively small and made of plastic using 3D printers. These robots cannot withstand experiments in external environments such as mountain trails or rubble, and they will easily break with intense movements. Although there is the advantage of being able to print parts by yourself, the large number of components makes replacing broken parts and maintenance very cumbersome. Therefore, in this study, we develop a metal quadruped robot MEVIUS, that can be constructed and assembled using only materials ordered through e-commerce. We have considered the minimum set of components required for a quadruped robot, employing metal machining, sheet metal welding, and off-the-shelf components only. Also, we have achieved a simple circuit and software configuration. Considering the communication delay due to its simple configuration, we experimentally demonstrate that MEVIUS, utilizing reinforcement learning and Sim2Real, can traverse diverse rough terrains and withstand outside experiments. All hardware and software components can be obtained from https://github.com/haraduka/mevius.