ロボット研究の評価とベンチマークのための反復・再現・複製実験フレームワークMIRRERの提案
Towards Using Multiple Iterated, Reproduced, and Replicated Experiments with Robots (MIRRER) for Evaluation and Benchmarking
ロボット研究における一般化性や再現性の評価が不足している問題に対し、性能評価・ベンチマーク・再現/複製実験を統合する概念フレームワークMIRRERを提案し、適用上の課題を整理した。
著者: Adam Norton, Brian Flynn
分類: cs.RO
原文アブストラクト
The robotics research field lacks formalized definitions and frameworks for evaluating advanced capabilities including generalizability (the ability for robots to perform tasks under varied contexts) and reproducibility (the performance of a reproduced robot capability in different labs under the same experimental conditions). This paper presents an initial conceptual framework, MIRRER, that unites the concepts of performance evaluation, benchmarking, and reproduced/replicated experimentation in order to facilitate comparable robotics research. Several open issues with the application of the framework are also presented.
