車輪とMEMSジャイロを用いた密結合単眼視覚オドメトリSLAM
Tightly-coupled Monocular Visual-odometric SLAM using Wheels and a MEMS Gyroscope
車輪エンコーダとMEMSジャイロの計測を事前積分して視覚最適化に密結合し、平面移動ロボット向けの高精度・頑健な単眼視覚オドメトリSLAMを実現した。
著者: Meixiang Quan, Songhao Piao, Minglang Tan, Shi-Sheng Huang
分類: cs.RO
原文アブストラクト
In this paper, we present a novel tightly-coupled probabilistic monocular visual-odometric Simultaneous Localization and Mapping algorithm using wheels and a MEMS gyroscope, which can provide accurate, robust and long-term localization for the ground robot moving on a plane. Firstly, we present an odometer preintegration theory that integrates the wheel encoder measurements and gyroscope measurements to a local frame. The preintegration theory properly addresses the manifold structure of the rotation group SO(3) and carefully deals with uncertainty propagation and bias correction. Then the novel odometer error term is formulated using the odometer preintegration model and it is tightly integrated into the visual optimization framework. Furthermore, we introduce a complete tracking framework to provide different strategies for motion tracking when (1) both measurements are available, (2) visual measurements are not available, and (3) wheel encoder experiences slippage, which leads the system to be accurate and robust. Finally, the proposed algorithm is evaluated by performing extensive experiments, the experimental results demonstrate the superiority of the proposed system.
