在路径规划时,为使机器人具有高精度定位能力,应考虑可定位性对规划路径的影响。在经典A*路径规划算法基础上,提出一种改进型A*路径规划方法,在搜索路径过程中考虑可定位性。引入克拉美-罗下界预测任一栅格定位方差的上界,将方差上界转化为定位信息熵描述可定位性。设计全新的代价函数,将可定位性纳入其中以综合评估搜索路径。结果表明:与经典A*算法相比,改进方法所得路径能成功避开可定位性差的区域,使路径规划结果具有更高的实用性。
Abstract
In path planning, the influence of positionability on path planning should be considered in order to make the robot have high-precision positioning ability. Based on the classical A* path planning algorithm, an improved A* path planning method was proposed, in which the localizability was considered in the process of searching the path. The Cramer-Luo lower bound was introduced to predict the upper bound of the positioning variance of any grid, and the upper bound of the variance was transformed into the entropy of positioning information to describe the localizability. A new cost function was designed, which incorporated localizability to comprehensively evaluate search directions. The results show that compared with the classical A* algorithm, the path obtained by the improved method can successfully avoid the poorly locatable regions, making the path planning result more practical.
关键词
可定位性 /
路径规划 /
A*算法 /
代价函数
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Key words
Localizability /
Path planning /
A* algorithm /
Cost function
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脚注
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基金
中央高校基金项目(3100102229103);中央高校基金项目(300104292209);国家自然科学基金青年科学基金项目(61503043);陕西省自然科学基金项目(2019JLP-07)
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