園芸環境における移動マニピュレータを用いた能動的セマンティックマッピング
Active Semantic Mapping with Mobile Manipulator in Horticultural Environments
RGB-Dカメラを搭載した移動マニピュレータで、確率的セマンティックマップと情報利得に基づく視点選択を行い、園芸環境のセマンティックマップを効率的に構築する手法を提案した。
著者: Jose Cuaran, Kulbir Singh Ahluwalia, Kendall Koe, Naveen Kumar Uppalapati, Girish Chowdhary
分類: cs.RO
原文アブストラクト
Semantic maps are fundamental for robotics tasks such as navigation and manipulation. They also enable yield prediction and phenotyping in agricultural settings. In this paper, we introduce an efficient and scalable approach for active semantic mapping in horticultural environments, employing a mobile robot manipulator equipped with an RGB-D camera. Our method leverages probabilistic semantic maps to detect semantic targets, generate candidate viewpoints, and compute corresponding information gain. We present an efficient ray-casting strategy and a novel information utility function that accounts for both semantics and occlusions. The proposed approach reduces total runtime by 8% compared to previous baselines. Furthermore, our information metric surpasses other metrics in reducing multi-class entropy and improving surface coverage, particularly in the presence of segmentation noise. Real-world experiments validate our method's effectiveness but also reveal challenges such as depth sensor noise and varying environmental conditions, requiring further research.
