Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (18): 58-62.DOI: 10.3778/j.issn.1002-8331.1908-0204

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Evaluation of Localizability for Path Planning

GAO Yang, LIU Jiang, LI Kunpeng   

  1. School of Automobile, Chang’an University, Xi’an 710054, China
  • Online:2020-09-15 Published:2020-09-10

路径规划的可定位性研究

高扬,刘江,李鹍鹏   

  1. 长安大学 汽车学院,西安 710054

Abstract:

A new path evaluation function is proposed to solve the shortcomings of traditional path planning which doesn’t consider the localizability of each point on the path. According to the characteristics of location error transfer in common location algorithms, the location variance can be represented by the location result in [X]-[Y] plane and the estimated variance of the orientation angle and then considering the path safety and length performance, the new path evaluation function is formed. The experimental results show that the evaluation function proposed in this paper can make the path planning obtain an overall optimal path in three aspects of localizability, safety and length.

Key words: path planning, localizability, mobile robot, evaluation function

摘要:

针对传统路径规划中没有将路径上各点的可定位性考虑进来,导致机器人在跟踪路径时由于定位误差过大导致跟踪失败,提出了一种新的路径评价函数将路径上各点可定位性进行考虑。分析常用定位算法中定位误差传递特性,采用将定位方差分别以[X]-[Y]平面定位结果的分布范围与朝向角的估计方差代表的方法,综合考虑路径安全性与长度性能,形成新的路径评价函数。实验结果表明,新的评价函数可以使得路径规划获得一条在可定位性、安全性、长度三方面总体最优的路径。

关键词: 路径规划, 可定位估计, 移动机器人, 评价函数