Toychain: A Simple Blockchain for Research in Swarm Robotics
Alexandre Pacheco, Ulysse Denis, Raina Zakir, Volker Strobel, Andreagiovanni Reina, Marco Dorigo
TL;DR
Toychain addresses the challenge of applying blockchain concepts to swarm robotics research by delivering a lightweight, Python-based blockchain framework tailored for simulator and real-world robot deployments. The approach uses a plug-in consensus architecture with PoW and PoA implementations and supports Python smart contracts, allowing researchers to experiment with distributed state and token economics in robotic swarms. It emphasizes simulator-time synchronization to accelerate experiments and offers easy integration with ARGoS, Gazebo, and ROS2. The results indicate comparable blockchain performance to Ethereum in swarm experiments and highlight the framework’s configurability and practicality for research, with open invitations for community contributions.
Abstract
This technical report describes the implementation of Toychain: a simple, lightweight blockchain implemented in Python, designed for ease of deployment and practicality in robotics research. It can be integrated with various software and simulation tools used in robotics (we have integrated it with ARGoS, Gazebo, and ROS2), and also be deployed on real robots capable of Wi-Fi communications. The Toychain package supports the deployment of smart contracts written in Python (computer programs that can be executed by and synchronized across a distributed network). The nodes in the blockchain can execute smart contract functions by broadcasting transactions, which update the state of the blockchain upon agreement by all other nodes. The conditions for this agreement are established by a consensus protocol. The Toychain package allows for custom implementations of the consensus protocol, which can be useful for research or meeting specific application requirements. Currently, Proof-of-Work and Proof-of-Authority are implemented.