Coopetitive Lunar Mapping: A distributed non-proprietary Multi-Robot Coordination using Blockchain-based Cost Optimisation

Recent advancements in in-situ resource utilization (ISRU) exploration lead to a new space economy trending towards coopetitive multi-robot systems (MRS). This trend highlights the need for a robust, transparent, and universally accessible cross-organization platform for coordinating these complex systems. To fill this gap, we present in this paper a novel approach to address the challenge of globally optimising distributed mapping tasks in coopetitive heterogeneous MRS within ISRU lunar scenarios. Thereby, we propose a cost function that combines the perspectives of both robotic operational metrics and economic principles to elevate ISRU global efficiency. Our approach leverages blockchain-based auctioning mechanisms to overcome the computational complexity of global coordination more efficiently. Our focus is on improving distributed mapping and utilizing blockchain technology to create a trustworthy digital platform for auction-based coordination. This non-proprietary and non-discriminatory platform aims to optimize costs in the context of ISRU. We demonstrate that our system outperforms traditional random task allocation methods by 17.5% on average. We validate our scenario in a simulated lunar environment, supporting robots with competing interests yet collaborating for mapping tasks.