Project emerge: an open source swarm robotics platform

University of Bologna
Italy
Computer Science
DOI: 10.18258/79978
$1,105
Raised of $1,000 Goal
110%
Funded on 9/12/25
Successfully Funded
  • $1,105
    pledged
  • 110%
    funded
  • Funded
    on 9/12/25

About This Project

Current swarm robotics research is limited by expensive, proprietary platforms costing hundreds per robot. We hypothesize that an open-source, low-cost design using 3D printing and affordable electronics can achieve comparable collective behaviors at <20% the cost. We will validate this by building and testing a 20-robot swarm demonstrating flocking and formation control, then releasing complete DIY specifications to democratize swarm robotics research globally.

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What is the context of this research?

Swarm robotics, where robots collaborate like a flock of birds, is a revolutionary field with the potential to solve major global challenges. However, the tools for exploring it are incredibly expensive and exclusive. A single research robot can cost thousands, confining this powerful technology to elite, well-funded labs.

This high barrier to entry stifles innovation. It prevents students, makers, educators, and independent researchers from learning, experimenting, and contributing their unique ideas.

Our project shatters this barrier. By combining the power of open-source with accessible technologies like 3D printing and affordable electronics, we are putting the tools of swarm robotics into the hands of everyone. We believe the next great breakthrough shouldn't be limited by a budget, but sparked by curiosity, anywhere in the world.

What is the significance of this project?

For Education: Students experience real collective intelligence - programming 20 robots to demonstrate flocking, consensus, and distributed coordination instead of just reading about AI concepts. This hands-on approach makes complex multi-agent systems tangible and inspiring.

For Research: True swarm behaviors emerge only with larger robot groups. While 20-robot Crazyflie swarms cost $3,000, our platform (3D printed robots) delivers similar capability for $600 - a 5x reduction that enables smaller institutions to conduct swarm experiments. Researchers can now study fundamental swarm algorithms, multi-robot coordination protocols, distributed decision-making, and scalable communication strategies. We're providing the foundational research tool (3D models, electronics, firmware and collective algorithms) for developing core principles that underlie all swarm applications, from search-and-rescue to environmental monitoring, rather than targeting specific domains directly.


What are the goals of the project?

  1. Build robot swarm: Create compact robots (15x7x12cm) with custom-designed electronics, firmware, 3D-printed chassis, and ArUco markers for vision-based tracking. Each robot is controlled via MQTT protocol through WiFi.

  2. Real collective behaviours: Using ScaFi [1] research software—a paradigm for programming distributed systems—we'll demonstrate flocking and formation control. Our external vision system tracks all robots simultaneously, enabling precise swarm coordination for European Researcher Night demonstrations.

  3. Release open-source toolkit: Publish refined 3D models, custom PCB designs, firmware code, ScaFi programming examples, and step-by-step assembly tutorials. This package enables anyone to replicate our swarm platform and contribute to the community of accessible swarm robotics research.

[1] Casadei, Roberto, et al. "Scafi: A scala DSL and toolkit for aggregate programming." SoftwareX 20 (2022)

Budget

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This funding is essential to advance our project from a single prototype to a validated multi-robot system. The budget items directly support the final phase of our research: large-scale experimental validation and public dissemination at the European Researchers' Night.

The funds will allow us to:

- Purchase a computer vision system (€200): A webcam and computing unit are required to track robot positions. This is crucial for collecting quantitative data to validate our multi-robot coordination algorithms.

- Build a 20-robot fleet (€800): Testing our system at scale requires a fleet of robots. This cost covers 3D-printed parts (€100) and all necessary electronics (motors, controllers, etc. at €700).

These components are indispensable for conducting our final experiments and successfully completing the project's demonstration and goals.

Endorsed by

As a researcher in aggregate programming and swarm intelligence, I am excited to endorse this project. It breaks the cost barrier that has long kept real swarm robotics out of reach for students, educators, and small labs. By pairing open-source tools with affordable, 3D-printed robots, it enables far wider participation in exploring, prototyping, and advancing collective behaviors, fueling innovation and the next generation of discoveries in distributed robotics.

Project Timeline

The success of this project requires two phases: production (scaling from prototype to 20 robots) and validation (testing emergent swarm behaviors that only appear with multiple robots). The European Researchers' Night deadline is fixed (26 September), creating time pressure. True collective intelligence remains uncertain until the production phase (which we plan to test on the 10th of September). We'll release open-source materials immediately after demonstration.

Aug 13, 2025

Project Launched

Sep 10, 2025

Phase 1: Production

Sep 26, 2025

Phase 2: Validation

Meet the Team

Gianluca Aguzzi
Gianluca Aguzzi
PhD in Computer Science

Affiliates

University of Bologna
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Nicolas Farabegoli
Nicolas Farabegoli
PhD Student in Computer Science

Affiliates

University of Bologna
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Gianluca Aguzzi

Gianluca Aguzzi is an Adjunct Professor in the Department of Computer Science and Engineering at the University of Bologna. He holds a PhD in Computer Science from the same institution. His primary research interests lie in the design and analysis of large-scale distributed systems, with a focus on swarm intelligence, collective adaptive systems, and swarm robotics.

He has authored more than 40 papers published in reputable international conferences and journals. Beyond his research, Professor Aguzzi is deeply committed to scientific outreach and public engagement. He has organized and participated in numerous public events, including the European Researchers' Night, and frequently delivers speeches on topics related to Artificial Intelligence for a general audience. He has also played an active role in the scientific community by co-organizing international conferences on large-scale systems.

Nicolas Farabegoli

Nicolas Farabegoli is a PhD student in Computer Science and Engineering at the University of Bologna, specializing in Pulverised Collective-Adaptive Systems. His research focuses on creating self-organizing distributed systems that can dynamically reconfigure themselves across cloud-edge continua, enabling applications from autonomous drone coordination to scalable IoT deployments.

His current research breakthroughs include developing macro-programming approaches for flexible cloud-edge coordination, creating declarative systems for automatic resource optimization, advancing algorithms for multi-drone wildlife tracking, and pioneering proximity-based self-federated learning for distributed AI.

Nicolas serves as a teaching tutor at the University of Bologna and maintains an active presence in the open-source development community. His research combines theoretical foundations with practical system implementations.

Beyond his academic pursuits, Nicolas has a passion for hardware design and implementation, including PCB design, electronics engineering, and embedded device development. As a Linux enthusiast, he leverages open-source technologies throughout his work. When not immersed in research, he enjoys playing tennis, mountain biking, and exploring creative projects through 3D printing and 3D modeling, which often complement his technical work by providing hands-on experience with rapid prototyping and design iteration.


Project Backers

  • 4Backers
  • 110%Funded
  • $1,105Total Donations
  • $276.25Average Donation
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