ROMR: A ROS-based Open-source Mobile Robot

TL;DR

ROMR is an affordable, open-source, ROS-compatible mobile robot platform utilizing off-the-shelf components, enabling accessible experimentation and development in autonomous navigation with a payload capacity of 90kg at under $1500.

Contribution

This work introduces ROMR, a low-cost, modular, open-source mobile robot platform that is fully compatible with ROS and uses readily available components, making autonomous robot research more accessible.

Findings

Validated through real-world experiments

Demonstrated effective SLAM integration

Cost less than $1500

Abstract

Currently, commercially available intelligent transport robots that are capable of carrying up to 90kg of load can cost \$5,000 or even more. This makes real-world experimentation prohibitively expensive and limits the applicability of such systems to everyday home or industrial tasks. Aside from their high cost, the majority of commercially available platforms are either closed-source, platform-specific or use difficult-to-customize hardware and firmware. In this work, we present a low-cost, open-source and modular alternative, referred to herein as "ROS-based Open-source Mobile Robot ($ROMR$)". $ROMR$ utilizes off-the-shelf (OTS) components, additive manufacturing technologies, aluminium profiles, and a consumer hoverboard with high-torque brushless direct current (BLDC) motors. $ROMR$ is fully compatible with the robot operating system (ROS), has a maximum payload of 90kg, and costs less than \$1500. Furthermore, ROMR offers a simple yet robust framework for contextualizing simultaneous localization and mapping (SLAM) algorithms, an essential prerequisite for autonomous robot navigation. The robustness and performance of the $ROMR$ were validated through real-world and simulation experiments. All the design, construction and software files are freely available online under the GNU GPL v3 licence at https://doi.org/10.17605/OSF.IO/K83X7. A descriptive video of $ROMR$ can be found at https://osf.io/ku8ag.