Robohub.org
 

mROBerTO: The modular millirobot for swarm behavior studies


by
26 October 2016



share this:
mroberto-title-view-miniature

Developed by a team at the University of Toronto, mROBerTO (milli-ROBot TORonto) is designed for swarm-robotics researchers who might wish to test their collective-behavior algorithms with real physical robots. With just a 16 mm x 16 mm footprint, mROBerTO can be used in a multitude of other miniature robot projects too—its modular design allowing for easy addition or removal of components.

mROBerTOs can determine any nearby robots’ relative distances and bearings by their unique robot IDs (up to 150 mm sensing radius) with the use of modulated IR signals. To achieve this, mROBerTO has an all-around coverage of IR phototransistors and emitters that can receive and send modulated IR signals. Furthermore, mROBerTO is equipped with Bluetooth Smart and ANT Wireless communication capabilities, which allow point-to-point and mesh network communication among robots. As for movement, there are two small motors located at the back of the robot that act as wheels and move the robot in a differential-drive configuration.

mROBerTO modular components. Image: University of Toronto

mROBerTO modular components. Image: University of Toronto

The majority of swarm robotics research has so far been limited to running virtual simulations for the purpose gathering experimental data. In order to test swarm behavior algorithms in a more realistic setting, we have to use physical robots in an environment where real-world constraints act upon the experiments. However, a swarm will often consist of tens—even hundreds—of robots operating together. So robots should ideally be as small as possible if these swarm algorithms are to be tested in a lab setting with limited work-space. And since we need a large number of these robots for experiments, we should aim to use only off-the-shelf components for easy assembly, production, and maintenance. In addition, certain swarm algorithms may require special sensing capabilities in the swarm robots, requiring modular in-design to allow quick exchanges of processing and sensing hardware. mROBerTO was designed to address these specific issues.

At the moment, there are no commercially available mROBerTOs. The BoM costs approximately 60 USD, and the source files of both the hardware and software can be provided by the developers. mROBerTOs were developed using the Eclipse IDE with SEGGER J-Link programmer/debugger but any integrated development environment that supports ARM GCC can be used to develop on mROBerTOs. For wireless debugging and development purposes, we recommend the user getting an nRF51 or nRF52 development board to wirelessly communicate with mROBerTOs.

mROBerTO was developed by Goldie NejatJustin Y. Kim, Tyler Colaco, Zendai Kashino and Beno Benhabib at the University of Toronto, Department of Mechanical Engineering. The latest version of the robot was completed in June 2016 and first featured in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) as ‘mROBerTO: A Modular Millirobot for Swarm-Behavior Studies’.


If you liked this article, you may also want to read these other articles on swarm robotics:

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.



tags: , , , , , ,


Justin Kim is a graduate researcher of Mechatronics Engineering working in the Computer Integrated Manufacturing Lab and the Autonomous Systems and Biomechatronics Lab at the University of Toronto...
Justin Kim is a graduate researcher of Mechatronics Engineering working in the Computer Integrated Manufacturing Lab and the Autonomous Systems and Biomechatronics Lab at the University of Toronto...

            AUAI is supported by:



Subscribe to Robohub newsletter on substack



Related posts :

Developing active and flexible microrobots

  13 May 2026
This class of robots opens up possibilities for biomedical applications.

How to teach the same skill to different robots

  11 May 2026
A new framework to teach a skill to robots with different mechanical designs, allowing them to carry out the same task without rewriting code for each.

Robot Talk Episode 155 – Making aerial robots smarter, with Melissa Greeff

  08 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Melissa Greeff from Queen's University about autonomous navigation and learning for drones.

New understanding of insect flight points way to stable flapping-wing robots

  07 May 2026
The way bugs and birds flap their wings may look effortless, but the dynamics that keep them aloft are dizzyingly complex and difficult to quantify.

Robotically assembled building blocks could make construction more efficient and sustainable

  05 May 2026
Research suggests constructing a simple building from interlocking subunits should be mechanically feasible and have a much smaller carbon footprint.

Robot Talk Episode 154 – Visual navigation in insects and robots, with Andrew Philippides

  01 May 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Andrew Philippides from the University of Sussex about what we can learn from ants and bees to improve robot navigation.

Ultralightweight sonar plus AI lets tiny drones navigate like bats

  29 Apr 2026
Researchers develop ultrasound-based perception system inspired by bat echolocation.

Gradient-based planning for world models at longer horizons

  28 Apr 2026
What were the problems that motivated this project and what was the approach to address them?



AUAI is supported by:







Subscribe to Robohub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence