VINet: 視覚・慣性情報に基づく地形分類と未知地形への適応ナビゲーション
VINet: Visual and Inertial-based Terrain Classification and Adaptive Navigation over Unknown Terrain
視覚と慣性センサを組み合わせて走行可能な地形を分類し、未知の地形でも適応的に制御できるナビゲーション手法を提案した論文。
著者: Tianrui Guan, Ruitao Song, Zhixian Ye, Liangjun Zhang
分類: cs.RO, cs.CV
原文アブストラクト
We present a visual and inertial-based terrain classification network (VINet) for robotic navigation over different traversable surfaces. We use a novel navigation-based labeling scheme for terrain classification and generalization on unknown surfaces. Our proposed perception method and adaptive scheduling control framework can make predictions according to terrain navigation properties and lead to better performance on both terrain classification and navigation control on known and unknown surfaces. Our VINet can achieve 98.37% in terms of accuracy under supervised setting on known terrains and improve the accuracy by 8.51% on unknown terrains compared to previous methods. We deploy VINet on a mobile tracked robot for trajectory following and navigation on different terrains, and we demonstrate an improvement of 10.3% compared to a baseline controller in terms of RMSE.
