1枚の地図で全部見つける：ゼロショット多物体ナビゲーションのためのリアルタイムオープンボキャブラリマッピング
One Map to Find Them All: Real-time Open-Vocabulary Mapping for Zero-shot Multi-Object Navigation
ロボットが過去の探索で得た情報を再利用できるオープンボキャブラリ特徴マップを構築し、確率的意味更新で誤りを抑えつつ複数物体を効率的に探索する手法を提案。実機でもリアルタイム動作し、単一・複数物体ナビゲーションで既存手法を上回る。
著者: Finn Lukas Busch, Timon Homberger, Jesús Ortega-Peimbert, Quantao Yang, Olov Andersson
分類: cs.RO, cs.AI
原文アブストラクト
The capability to efficiently search for objects in complex environments is fundamental for many real-world robot applications. Recent advances in open-vocabulary vision models have resulted in semantically-informed object navigation methods that allow a robot to search for an arbitrary object without prior training. However, these zero-shot methods have so far treated the environment as unknown for each consecutive query. In this paper we introduce a new benchmark for zero-shot multi-object navigation, allowing the robot to leverage information gathered from previous searches to more efficiently find new objects. To address this problem we build a reusable open-vocabulary feature map tailored for real-time object search. We further propose a probabilistic-semantic map update that mitigates common sources of errors in semantic feature extraction and leverage this semantic uncertainty for informed multi-object exploration. We evaluate our method on a set of object navigation tasks in both simulation as well as with a real robot, running in real-time on a Jetson Orin AGX. We demonstrate that it outperforms existing state-of-the-art approaches both on single and multi-object navigation tasks. Additional videos, code and the multi-object navigation benchmark will be available on https://finnbsch.github.io/OneMap.
