Finding an alternative way to replace the magnetic compass to determine the robot heading angle indoor is always a challenge in the robotics society. This brief proposes a structurally simple yet efficient nonmagnetic heading determination system, which can be used in the planar indoor environment with abundant ferromagnetic and electromagnetic interferences, by the combination of gyroscope and vision. The gyroscope is utilized to perceive the yaw rate, whereas a downward-looking camera is used to capture the prelaid auxiliary strips to acquire the absolute angle of the robot heading. Due to the existence of pseudomeasurement, varying noise statistical characteristics, and asynchronization between state propagation and measurement, the existing Kalman filters cannot be applied to fuse the gyroscopic and visual data. Therefore, a novel fusion algorithm named pseudomeasurement-resistant adaptive asynchronous Kalman filter is proposed, which is experimentally verified to be efficient in the environment with various interferences.

中文翻译：

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一种新型轮式移动机器人惯性视觉航向确定系统

寻找替代磁罗盘的替代方法来确定室内机器人的航向角始终是机器人社会的挑战。本文提出了一种结构简单但高效的非磁航向确定系统，该系统可以通过陀螺仪和视觉的结合，用于铁磁和电磁干扰丰富的平面室内环境。陀螺仪用于感知偏航率，而向下看的相机用于捕获预先铺设的辅助条带以获得机器人航向的绝对角度。由于伪测量的存在、变化的噪声统计特性以及状态传播和测量之间的异步性，现有的卡尔曼滤波器不能用于融合陀螺和视觉数据。所以，