移动机器人里程计非系统误差不确定性分析方法

移动机器人里程计非系统误差建模是研究移动机器人定位问题的基础。现有的移动机器人里程计非系统误差建模方法多数针对某一种驱动类型移动机器人设计，运动过程中缺乏对里程计累计误差的实时反馈补偿功能，经过长距离运动过程定位精度大幅度降低。基于此，针对同步驱动和差动驱动轮式移动机器人平台提出一种通用的里程计非系统误差建模方法。在假设机器人运动路径近似弧线基础上，依据里程计误差传播规律推导非系统误差与里程计过程输入量之间的近似函数关系，进而对移动机器人位姿跟踪过程中产生的里程计累计误差给予实时反馈补偿。里程计非系统误差建模前后定位过程的对比试验表明，这种非系统误差实时补偿方法有效地减少了移动机器人导航过程中产生的里程计累计误差，提高了定位精度。

Analysis Approach to Odometric Non-systematic Error Uncertainty for Mobile Robots

Odometric non-systematic error modeling for mobile robot is the basis for researching the positioning of mobile robot. Most of the approaches to odometric non-systematic error modeling are designed for some special driving-type robot up to now. And the odometric long term errors without bound, which degrade positioning precision after long-distance movement, are not often capable of being compensated in real-time. Therefore, a general approach to odometric non-systematic error modeling for mobile robot is proposed with respect to both synchronous-drive robot and differential-drive robot. The method presents an assumption that the robot path is approximated to circular arcs. The approximate function relationships between the process input of odometry and non-systematic error are derived based on the odometric error transformations rules, further the approach is applied to pose tracking for mobile robots, which is online used to compensate the accumulative errors of odometry in the process of positioning. The contrast experiments before and after odometric non-systematic error modeling denote that the new approach reduces the accumulative error of odometry and improves the positioning precision efficiently.