未知環境での自律点検ミッションを強化する行動可能な階層的シーン表現
An Actionable Hierarchical Scene Representation Enhancing Autonomous Inspection Missions in Unknown Environments
未知環境での点検ミッションにおいて、多分解能のシーン表現と計画の基盤を提供する階層的シーングラフ（LSG）を提案し、マルチモーダルな点検・探索プランナーと統合して、シミュレーションと実機実験で有効性を示した。
著者: Vignesh Kottayam Viswanathan, Mario Alberto Valdes Saucedo, Sumeet Gajanan Satpute, Christoforos Kanellakis, George Nikolakopoulos
分類: cs.RO
原文アブストラクト
In this article, we present the Layered Semantic Graphs (LSG), a novel actionable hierarchical scene graph, fully integrated with a multi-modal mission planner, the FLIE: A First-Look based Inspection and Exploration planner. The novelty of this work stems from aiming to address the task of maintaining an intuitive and multi-resolution scene representation, while simultaneously offering a tractable foundation for planning and scene understanding during an ongoing inspection mission of apriori unknown targets-of-interest in an unknown environment. The proposed LSG scheme is composed of locally nested hierarchical graphs, at multiple layers of abstraction, with the abstract concepts grounded on the functionality of the integrated FLIE planner. Furthermore, LSG encapsulates real-time semantic segmentation models that offer extraction and localization of desired semantic elements within the hierarchical representation. This extends the capability of the inspection planner, which can then leverage LSG to make an informed decision to inspect a particular semantic of interest. We also emphasize the hierarchical and semantic path-planning capabilities of LSG, which could extend inspection missions by improving situational awareness for human operators in an unknown environment. The validity of the proposed scheme is proven through extensive evaluations of the proposed architecture in simulations, as well as experimental field deployments on a Boston Dynamics Spot quadruped robot in urban outdoor environment settings.
