基于偏振光传感器的仿鼠脑导航方法

A Bionic Rat Brain Navigation Method Based on Polarization Sensor

面对长距离复杂场景下的自主移动机器人导航问题,仿生鼠脑的RatSLAM相较传统SLAM更加高效。但完全依赖视觉信息,导致其精度不高、可靠性不足。通过引入天空偏振光定向,高效地提供精准的绝对航向角,可以弥补RatSLAM的不足。设计并搭建了一种偏振光仿鼠脑导航系统及导航实验平台,经过室外道路实验验证了系统的性能,并与RatSLAM进行了比较。实验结果表明,偏振光仿鼠脑导航系统和RatSLAM的平均位置误差分别为3.65 m和26.29 m,平均角度误差分别为0.36°和2.39°。该系统减少了累积误差,实现了高效、强鲁棒性、轻量化的自主导航。

For autonomous mobile robot navigation in long-distance complex environments,RatSLAM,which simulates rat brain,is more efficient than traditional SLAM.However,it completely relies on visual information,resulting in its low accuracy and insufficient reliability.By introducing polarization skylight for orientation,which efficiently provides precise absolute heading angles,RatSLAM can be compensated.A polarization skylight bionic rat brain navigation system and an experimental platform are designed.The performance of the system is verified through outdoor road experiments,and is compared with that of the RatSLAM.The experimental results show that the mean position errors of the polarization skylight bionic rat brain navigation system and RatSLAM are respectively 3.65 m and 26.29 m,and the mean angle errors are respectively 0.36° and 2.39°.This system reduces cumulative error and achieves efficient,robust and lightweight autonomous navigation.