スマートフォン搭載IMUによる歩行者モーショントラッキング
Pedestrian Motion Tracking by Using Inertial Sensors on the Smartphone
スマホのIMU信号のみから歩行者の平面位置・速度・進行方向を推定する手法を提案し、学習ベースでEKFの観測ノイズを動的調整、公開データセットで高精度を実証した。
著者: Yingying Wang, Hu Cheng, Max Q. H. Meng
分類: cs.RO
原文アブストラクト
Inertial Measurement Unit (IMU) has long been a dream for stable and reliable motion estimation, especially in indoor environments where GPS strength limits. In this paper, we propose a novel method for position and orientation estimation of a moving object only from a sequence of IMU signals collected from the phone. Our main observation is that human motion is monotonous and periodic. We adopt the Extended Kalman Filter and use the learning-based method to dynamically update the measurement noise of the filter. Our pedestrian motion tracking system intends to accurately estimate planar position, velocity, heading direction without restricting the phone's daily use. The method is not only tested on the self-collected signals, but also provides accurate position and velocity estimations on the public RIDI dataset, i.e., the absolute transmit error is 1.28m for a 59-second sequence.
