動的ヒルベルトマップ：変化する環境におけるリアルタイム占有予測
Dynamic Hilbert Maps: Real-Time Occupancy Predictions in Changing Environment
移動物体の空間的不確かさを高次元特徴空間の連続占有マップに組み込み、動的環境の瞬時占有状態と将来予測をリアルタイムに行う手法を提案した。
著者: Vitor Guizilini, Ransalu Senanayake, Fabio Ramos
分類: cs.RO, cs.LG
原文アブストラクト
This paper addresses the problem of learning instantaneous occupancy levels of dynamic environments and predicting future occupancy levels. Due to the complexity of most real-world environments, such as urban streets or crowded areas, the efficient and robust incorporation of temporal dependencies into otherwise static occupancy models remains a challenge. We propose a method to capture the spatial uncertainty of moving objects and incorporate this uncertainty information into a continuous occupancy map represented in a rich high-dimensional feature space. Experiments performed using LIDAR data verified the real-time performance of the algorithm.
