スキルグラフ表現を用いたロボット組立の自律的統合と改善
Autonomous Integration and Improvement of Robotic Assembly using Skill Graph Representations
ロボット組立システムの統合と性能改善を自動化するフレームワークを提案。スキルグラフ表現により、意味レベルでの計画と実行を結びつけ、データ収集と閉ループ改善を可能にする。
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著者: Peiqi Yu, Philip Huang, Chaitanya Chawla, Guanya Shi, Jiaoyang Li, Changliu Liu
分類: cs.RO
原文アブストラクト
Robotic assembly systems traditionally require substantial manual engineering effort to integrate new tasks, adapt to new environments, and improve performance over time. This paper presents a framework for autonomous integration and continuous improvement of robotic assembly systems based on Skill Graph representations. A Skill Graph organizes robot capabilities as verb-based skills, explicitly linking semantic descriptions (verbs and nouns) with executable policies, pre-conditions, post-conditions, and evaluators. We show how Skill Graphs enable rapid system integration by supporting semantic-level planning over skills, while simultaneously grounding execution through well-defined interfaces to robot controllers and perception modules. After initial deployment, the same Skill Graph structure supports systematic data collection and closed-loop performance improvement, enabling iterative refinement of skills and their composition. We demonstrate how this approach unifies system configuration, execution, evaluation, and learning within a single representation, providing a scalable pathway toward adaptive and reusable robotic assembly systems. The code is at https://github.com/intelligent-control-lab/AIDF.
