Robot swarms neutralize harmful Byzantine robots using a blockchain-based token economy

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 (e.g., 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. In this paper, 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 use blockchain technology, originally developed for the digital currency Bitcoin. The robots are given crypto tokens that allow them to participate in the swarm's security-critical activities. The token economy is regulated via a smart contract that decides how to distribute crypto tokens among the robots depending on their contributions. We design the smart contract so that Byzantine robots soon ..., Results obtained in both simulated and real-robot experiments., , # Robot swarms neutralize harmful Byzantine robots using a blockchain-based token economy

This dataset contains the results of the simulation and real-robot experiments, which are discussed in the Science Robotics article \"Robot swarms neutralize harmful Byzantine robots using a blockchain-based token economy.\"

## Description of the data and file structure

The dataset is divided into two top-level folders, `reality` and `simulation`, corresponding to the results of the real-robot and simulation experiments, respectively.

For both top-level folders, there are sub-folders for the different experiments (named `Experiment_Gx`) that correspond to the experiments described in the article as follows:

* `Experiment_G1`: Experiment 1a - Increasing number of Byzantines
* `Experiment_G2`: Experiment 1b - Generality study (changing floor layouts)
* `Experiment_G3`: Experiment 1b - Generality study (p=0.5)
* `Experiment_G4`: Experiment 1b - Generality study (uniform distribution between...