摘要
为解决仅仅利用视觉系统或者声纳系统得到的信息进行机器人自定位时存在较大的误差的问题,提出了一种极坐标系下进行自定位的方法.在极坐标系下,通过简单的几何算法获得视觉距离和角度、码盘距离和角度及声纳距离和角度,然后运用模糊数学的方法再对其信息融合,即将机器人视觉信息,驱动码盘信息和声纳信息等进行有效的融合,得到了理想的距离和角度信息,从而提高机器人的自定位精度.实验结果表明:在4 m范围内,其定位误差低于1.5%.该研究为多机器人定位提供了参考依据.
To solve the problem that using the information of the robot vision or sonar system can not give good self-localization result, a new self-localization method for autonomous mobile robot （AMR） is proposed under polar coordinates. In this way, the distances and the angles of vision, driving motors and the sonar respectively can be derived from the simple geometrical algorithm, then, using the method of fuzzy mathematics to fuse the information. Thus the ideal distance and the angle information can be obtained to improve the self-localization accuracy of AMR. Experimental results show that the localization error is lower than 1.5% in the range of 4 m, and that the method provides a reference for the self-localization of multiple robots.
出处
《中北大学学报（自然科学版）》
CAS
北大核心
2009年第3期233-237,共5页
Journal of North University of China(Natural Science Edition)
基金
山西省留学回国人员科研基金资助项目
关键词
机器人自定位
信息融合
极坐标系
声纳
视觉信息处理
robot self-localization
information fusion
polar coordinates
sonar
information processing of vision
