A Practical Framework of Key Performance Indicators for Multi-Robot Lunar and Planetary Field Tests
🤖 AI Summary
This study addresses the lack of a unified, science-driven performance evaluation framework for multi-robot planetary exploration, which hinders meaningful cross-system comparisons. To bridge this gap, the work proposes the first science-oriented key performance indicator (KPI) framework tailored to three realistic lunar multi-robot cooperative scenarios. The framework is hierarchically structured around three dimensions—efficiency, robustness, and accuracy—and has been deployed and validated in field trials. It effectively narrows the divide between engineering metrics and scientific objectives: efficiency and robustness metrics prove readily applicable, while accuracy metrics remain constrained by the difficulty of obtaining ground-truth data. Overall, the framework serves as a standardized tool to advance the evaluation and optimization of robotic systems for planetary exploration.
Application Category
📝 Abstract
Robotic prospecting for critical resources on the Moon, such as ilmenite, rare earth elements, and water ice, requires robust exploration methods given the diverse terrain and harsh environmental conditions. Although numerous analog field trials address these goals, comparing their results remains challenging because of differences in robot platforms and experimental setups. These missions typically assess performance using selected, scenario-specific engineering metrics that fail to establish a clear link between field performance and science-driven objectives. In this paper, we address this gap by deriving a structured framework of KPI from three realistic multi-robot lunar scenarios reflecting scientific objectives and operational constraints. Our framework emphasizes scenario-dependent priorities in efficiency, robustness, and precision, and is explicitly designed for practical applicability in field deployments. We validated the framework in a multi-robot field test and found it practical and easy to apply for efficiency- and robustness-related KPI, whereas precision-oriented KPI require reliable ground-truth data that is not always feasible to obtain in outdoor analog environments. Overall, we propose this framework as a common evaluation standard enabling consistent, goal-oriented comparison of multi-robot field trials and supporting systematic development of robotic systems for future planetary exploration.
Problem
Research questions and friction points this paper is trying to address.
Key Performance Indicators
multi-robot systems
planetary exploration
field testing
performance evaluation
Innovation
Methods, ideas, or system contributions that make the work stand out.
Key Performance Indicators
multi-robot systems
planetary exploration
field testing
performance evaluation
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