ロボット視覚によるシーン理解チャレンジ
The Robotic Vision Scene Understanding Challenge
シミュレーション上で能動的なロボットによる3Dシーン理解を評価する新しいベンチマークを提案し、2種類のタスク・3難易度・5環境と新しい評価指標を提供する。
著者: David Hall, Ben Talbot, Suman Raj Bista, Haoyang Zhang, Rohan Smith, Feras Dayoub, Niko Sünderhauf
分類: cs.RO
原文アブストラクト
Being able to explore an environment and understand the location and type of all objects therein is important for indoor robotic platforms that must interact closely with humans. However, it is difficult to evaluate progress in this area due to a lack of standardized testing which is limited due to the need for active robot agency and perfect object ground-truth. To help provide a standard for testing scene understanding systems, we present a new robot vision scene understanding challenge using simulation to enable repeatable experiments with active robot agency. We provide two challenging task types, three difficulty levels, five simulated environments and a new evaluation measure for evaluating 3D cuboid object maps. Our aim is to drive state-of-the-art research in scene understanding through enabling evaluation and comparison of active robotic vision systems.
