複数歩行者を含むフォトリアル環境の高速プロトタイピングフレームワーク
A Framework for Fast Prototyping of Photo-realistic Environments with Multiple Pedestrians
Unreal EngineとAirSim上で歩行者と移動ロボットのフォトリアルなシナリオを簡単に生成できるフレームワークを開発し、多目標追跡のユースケースで有用性を示した。
著者: Sara Casao, Andrés Otero, Álvaro Serra-Gómez, Ana C. Murillo, Javier Alonso-Mora, Eduardo Montijano
分類: cs.RO
原文アブストラクト
Robotic applications involving people often require advanced perception systems to better understand complex real-world scenarios. To address this challenge, photo-realistic and physics simulators are gaining popularity as a means of generating accurate data labeling and designing scenarios for evaluating generalization capabilities, e.g., lighting changes, camera movements or different weather conditions. We develop a photo-realistic framework built on Unreal Engine and AirSim to generate easily scenarios with pedestrians and mobile robots. The framework is capable to generate random and customized trajectories for each person and provides up to 50 ready-to-use people models along with an API for their metadata retrieval. We demonstrate the usefulness of the proposed framework with a use case of multi-target tracking, a popular problem in real pedestrian scenarios. The notable feature variability in the obtained perception data is presented and evaluated.
