融合轮速因子的视觉惯导定位算法

Visual Inertial Navigation Positioning Algorithm Integrating Wheel Speed Factor

提出了一种通过视觉、惯性测量单元(IMU)、轮速计信息的紧密融合的定位算法,以应对在地面移动平台上应用视觉惯性定位系统面临尺度估计退化和定位性能下降的挑战。结果表明,融合轮速因子的视觉惯导定位算法有效解决了尺度不确定性问题,显著提升了地面移动平台定位的准确性和鲁棒性。

A positioning algorithm that tightly integrates visual,inertial measurement unit(IMU),and wheel speedometer information has been proposed to address the challenges of scale estimation degradation and reduced positioning performance faced by visual inertial positioning systems applied on ground mobile platforms.The results show that the visual inertial navigation positioning algorithm integrating wheel speed factors effectively solves the problem of scale uncertainty and significantly improves the accuracy and robustness of ground mobile platform positioning.