ROMR: A ROS-based Open-source Mobile Robot

TL;DR

ROMR addresses the prohibitively high cost and closed nature of commercial ITR platforms by delivering a low-cost open-source mobile robot built from off-the-shelf components. It combines a ROS-based software stack with a modular hardware design featuring a Nvidia Jetson Nano, Arduino Mega, dual BLDC hoverboard motors, RealSense cameras, LiDAR, and a 36V battery, enabling payloads up to 90 kg for research and logistics. The paper provides comprehensive build instructions, design files, and validation in simulation and real-world tests, including SLAM integration using Hector-SLAM and AMCL for 2D localization and mapping. The open-source release under GNU GPL v3, together with ROS-based teleoperation and gesture control, lowers barriers for replication and rapid development of autonomous mobile robots.

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.

Figures (10)

• Figure 1: $ROMR$ is built from consumer hoverboard wheels with high torque brushless direct current (BLDC) motors. It utilises Arduino Mega Rev3, an Nvidia jetson Nano, and the components described in Tables \ref{['tab:5']} and \ref{['tab:6']}. (a) front view (b) side view (c) back view.
• Figure 8: The $ROMR$ hardware architecture is based on an ODrive board (light green) to actuate the motors, an Nvidia Jetson Nano (light blue) as a computing interface for high-level tasks, an Arduino Mega Rev3 (orange) as low-level computing interface.
• Figure 12: The $ROMR$ real-time control and monitoring with ROS-Mobile device (a) System communication structure (b) Control and monitoring from ROS-Mobile rottmann2020ros or Android-based devices.
• Figure 13: $ROMR$ real-time control and monitoring based on hand movement (a) hand tilt forward $\rightarrow$ the robot moves forward (b) hand tilt backwards $\rightarrow$ the robot moves back (c) hand tilt to the right $\rightarrow$ the robot rotates in a clockwise direction (d) hand tilt to the left $\rightarrow$ the robot rotates in a counter-clockwise direction.
• Figure 14: Block diagram illustrating the architecture and flow of information during the gesture control approach.