Blockchain-based robotics: A new way to generate trust between humans and robots

Swarms of robots have the potential to revolutionize a wide variety of industries, from transportation and agriculture to search and rescue. The vision is of driverless cars moving as a single, hive-mind intelligence—anticipating demand, reducing congestion and stopping accidents—or drone swarms flooding into a disaster zone to locate survivors and map danger zones.

On paper, the technology is here. But fundamental concerns of trust, security and reliability have prevented this futuristic technology from leaving the safe confines of academia. What happens if a malfunctioning drone feeds bad data to woodland firefighters, diverting them into a lethal hot zone? Or a hacker takes control of your driverless car, threatening to plow it into traffic if you don’t transfer them $1,000 in bitcoin? The consequences of this technology going wrong carry profound human, logistical and economic risks.

The core vulnerability of a robot swarm, or any kind of complex peer-to-peer system without a strict hierarchy, is its interconnectedness; as robots feed data to one another, they create a cascade of potential failure points. The failure of a single robot is a contained problem; you switch it off. But one bad actor in a swarm is a system-wide threat. It doesn't just go offline; it poisons the entire network with misinformation.

At IE University, the solution doesn't come from building better robots, but from designing a better way for them to communicate. For Dr. Eduardo Castelló, Assistant Professor of Robotics, the solution lies in blockchain technology—a “hidden gem” largely overlooked in robotics—that fundamentally changes how robots interact. Instead of “robots sharing information and communicating with one another,” he explains, they learn to “transact.”

On a blockchain, peers transact directly with no central authority governing the process. Information is grouped into blocks that are linked sequentially to form an immutable, unbreakable chain. While best known for transacting money—Bitcoin has run for over fifteen years without interruption—this protocol can also secure valuable assets like data and code.

The blockchain’s decentralized design is what makes this new form of communication so secure. Because data is replicated and distributed across the entire network, it becomes practically impossible for a single bad actor—be it a hacker or a malfunctioning robot—to alter or fake information without being detected. This creates a tamper-proof log of all transactions. When this log is made public, it ensures transparency, allowing the entire swarm (and its human supervisors) to access the data and verify its integrity.

A blueprint for a trustworthy swarm

Dr. Castelló's research, conducted in collaboration with MIT, showcases the potential of blockchain-based robotics by addressing the logistical challenge of shared e-bike networks. In cities across the world, fleets of bikes become concentrated in commercial districts after the morning rush, cluttering sidewalks and leaving other neighborhoods underserved. Sending trucks to manually rebalance the fleet is expensive, slow and polluting. 

Taking inspiration from hive-minded insects, Dr. Castelló’s modeling has shown how a fleet of autonomous bikes could rebalance itself by leaving “virtual pheromone trails.” Without reliance on a central server, idle bikes can effectively “smell” high-demand routes and navigate there automatically by transforming into a tricycle for increased stability.“It’s basically copying what works already in nature—for example, the collective behavior of bees and ants—and applying that to robots,” he explains.

This approach has shown its efficacy in realistic modeling, and the underlying principles could one day be applied to managing entire fleets of autonomous cars. But what happens if a single rogue bike, sending bad data, tells the swarm to congregate in an empty parking lot? This is where blockchain provides a range of solutions. 

Firstly, the system polices itself through a reputation-based economy. Undertaking an action costs a digital token, and if a rogue bike broadcasts a lie—claiming an empty lot is a high-demand hub—the swarm’s own data will flag it as a falsehood and the bike loses its token. To obtain definitive proof, another robot can physically check the location. By continuously sending false data, a bad actor will deplete its tokens and be cut off from the network—all without human intervention.

Secondly, the blockchain provides a permanent audit trail on a shared ledger that no one can alter. Unlike the opaque and fragmented logs of modern software, this gives an engineer a clear record of who said what and when, making diagnostics straightforward. Significantly, this unchangeable history is what also allows the swarm to heal itself: a misled robot can retrace the events, find the original lie and autonomously course correct.

Finally, the system enables “blind collaboration.” A robot can be given a simple instruction—“place this brick on top of that brick”—without ever knowing the full mission is to build a skyscraper. This is made possible by using a cryptographic data structure known as a Merkle Tree. Each robot is sent its individual task along with a signature that it can check against the overall mission blueprint to verify its orders are authentic.

While this secrecy may seem excessive for e-bike rebalancing, the principle is critical for high-stakes operations. A swarm of drones cleaning up nuclear waste, for instance, cannot afford to reveal the location of every piece of radioactive material if a single unit is compromised.

But for all its promise, Dr. Castelló emphasizes that blockchain is not a magic bullet. The technology is computationally-intensive, and if public blockchain networks are used, transactions can be slow. The solution, he argues, lies in its strategic use.

For constant, low-stakes information—like bikes updating their locations every second—the system uses faster, lightweight cryptographic methods. But for mission-critical data, such as confirming the final location of nuclear material, the system relies on heavier cryptographic methods which entail more security. This hybrid approach ensures the system is both responsive enough for the real world and secure enough to be trusted.

The robot entrepreneur

With blockchain providing the foundation for secure, cooperative and self-sufficient robotic systems, the team at IE University is pursuing a radical end goal. They aim to create an entirely new type of robot: one that can act as an entrepreneur.

This vision is structured around the concept of Decentralized Autonomous Robotic Organization, or DARO. In essence, a DARO is a robot that runs its own business. It can earn its own income—by managing city trash or harvesting crops—and then autonomously reinvest that money to purchase supplies, upgrade its own hardware and deliver a return to its human investors. 

While it may sound like science fiction, this vision is built on a proven foundation. During his time at MIT, Dr. Castelló co-developed a proof-of-concept: a self-employed robot artist named Gaka-chu. The team repurposed a standard industrial arm—formerly used on a car assembly line—replacing its driller attachment with a paintbrush and teaching it to paint. The robot autonomously created paintings and sold them at online auctions. It used the cryptocurrency it earned to pay for supplies, repay its investors and even hire a human assistant— all without direct human supervision.

Building upon this foundational work, Dr. Castelló and his team at IE University are now exploring how to create more complex organizations such as “robot cooperatives” within the ROBOPRENEUR research line. This allows individual DAROs to team up and even contract one another to tackle complex problems. For instance, a fleet of cleaning bots could autonomously hire a transportation bot to haul away the waste, creating a machine-to-machine economy. 

Demonstrating the versatility of blockchain-based robotics, the blind collaboration feature could also be used in this context. This feature offers more than just mission security; it also creates a marketplace that is resilient against corruption. Because each robot is programmed to know only its specific task—not the wider project or the identity of its collaborators—its human owners cannot conspire to fix prices or rig outcomes, allowing even untrusting competitors to cooperate effectively.

These innovations have far-reaching consequences, fundamentally changing our relationship with technology. Robots would no longer be mere tools, but economic peers operating alongside us. The role of the human shifts from operator to strategist: setting the mission, but letting the robot run the business autonomously.

From lab to marketplace

The Cyber-Physical Life Research Group, founded by Dr. Castelló at IE University, functions like a creative sandbox for the future. It is guided by a philosophy of bridging the gap between the digital and physical worlds, and exploring, as Dr. Castelló puts it, “the interconnection of   research fields that, apparently, don't have much to do with each other, but together, do something very interesting.”

The student-led SPICE (Smart Projection Interface for Cooking Enhancement) project is a prime example of this concept in action. It addresses the limitations of screen-based interfaces for hands-on processes like cooking by using large vision models (LVMs) and a tracking system to project recipe information directly onto the cooking surface. This creates a Tangible User Interface (TUI) where digital instructions are overlaid onto the physical environment. Addressing the gap in research on TUIs for daily tasks, this innovative work was published in the prestigious SMC 2025 Conference, and its student lead has since launched a startup dedicated to fusing digital intelligence, like LLMs, with our physical world.

This futuristic, industry-focused mindset  is a core part of the lab's educational mission. Another student-led project, iTrash, is an intelligent trash can designed to improve campus recycling. When a user holds up an item, the device takes a picture, a LVM analyzes the image, and a robot indicates the correct bin. Successful recycling is rewarded with a cryptocurrency donation to the user’s favored charity—a project that led to a more than 34% increase in correct recycling on campus.

Furthermore, the lab maintains close ties to industry, collaborating with robotics firms like Robotnik, Pal Robotics and Husarion, using their hardware and blockchain companies like Ripple to test new concepts. The lab also invites companies for tours, offering them a fresh perspective on the future of their industries and building new partnerships. As Dr. Castelló explains: “Companies tell us, ‘Hey, this project is fantastic. Can we team up and extend this research to tackle this problem that we are having?”

Integrating blockchain and robotics: Pathways forward

It can’t be denied that implementing networked robotics poses certain risks, such as driverless cars being hacked or drones leading firefighters astray. The core vulnerability is not the robot but the fragile communication and control system it relies on. The very properties that make a swarm so interesting—decentralized control, emergent behavior, fault tolerance—can also backfire when conditions are not quite right, meaning a single bad actor can poison the entire system.

The work at IE University builds trust directly into the system’s foundation: an immutable ledger allows for self-correction, a reputation-based economy removes bad actors and blind collaboration ensures mission security. This model is already demonstrating its promise, enabling autonomous e-bikes to rebalance their fleet and a robot artist to earn its own money, pay for supplies and even hire a human assistant.

The fusion of blockchain and robotics, two seemingly disparate fields, does more than solve a technical problem. It creates the conditions for an entirely new economic actor: the robot entrepreneur. In doing so, it reframes the human role from operator to strategist, and our relationship with robots from control to partnership.