Article ; Online: Robot swarms neutralize harmful Byzantine robots using a blockchain-based token economy.
Science robotics
2023 Volume 8, Issue 79, Page(s) eabm4636
Abstract: Through cooperation, robot swarms can perform tasks or solve problems that a single robot from the swarm could not perform/solve by itself. However, it has been shown that a single Byzantine robot (such as a malfunctioning or malicious robot) can disrupt ...
| Abstract | Through cooperation, robot swarms can perform tasks or solve problems that a single robot from the swarm could not perform/solve by itself. However, it has been shown that a single Byzantine robot (such as a malfunctioning or malicious robot) can disrupt the coordination strategy of the entire swarm. Therefore, a versatile swarm robotics framework that addresses security issues in inter-robot communication and coordination is urgently needed. Here, we show that security issues can be addressed by setting up a token economy between the robots. To create and maintain the token economy, we used blockchain technology, originally developed for the digital currency Bitcoin. The robots were given crypto tokens that allowed them to participate in the swarm's security-critical activities. The token economy was regulated via a smart contract that decided how to distribute crypto tokens among the robots depending on their contributions. We designed the smart contract so that Byzantine robots soon ran out of crypto tokens and could therefore no longer influence the rest of the swarm. In experiments with up to 24 physical robots, we demonstrated that our smart contract approach worked: The robots could maintain blockchain networks, and a blockchain-based token economy could be used to neutralize the destructive actions of Byzantine robots in a collective-sensing scenario. In experiments with more than 100 simulated robots, we studied the scalability and long-term behavior of our approach. The obtained results demonstrate the feasibility and viability of blockchain-based swarm robotics. |
|---|---|
| Language | English |
| Publishing date | 2023-06-28 |
| Publishing country | United States |
| Document type | Journal Article |
| ISSN | 2470-9476 |
| ISSN (online) | 2470-9476 |
| DOI | 10.1126/scirobotics.abm4636 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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