環境の時間特性に適応する位置推定のためのセンサ窓長自動調整
Look No Further: Adapting the Localization Sensory Window to the Temporal Characteristics of the Environment
位置推定で使う時空間センサ窓の長さを、環境に応じて自動で変える手法を提案し、視覚・Wi-Fiのベンチマークで固定長より未定位距離を大幅に減らしつつ精度を維持できることを示した。
著者: Jake Bruce, Adam Jacobson, Michael Milford
分類: cs.RO
原文アブストラクト
Many localization algorithms use a spatiotemporal window of sensory information in order to recognize spatial locations, and the length of this window is often a sensitive parameter that must be tuned to the specifics of the application. This letter presents a general method for environment-driven variation of the length of the spatiotemporal window based on searching for the most significant localization hypothesis, to use as much context as is appropriate but not more. We evaluate this approach on benchmark datasets using visual and Wi-Fi sensor modalities and a variety of sensory comparison front-ends under in-order and out-of-order traversals of the environment. Our results show that the system greatly reduces the maximum distance traveled without localization compared to a fixed-length approach while achieving competitive localization accuracy, and our proposed method achieves this performance without deployment-time tuning.
