Implementation of a Kalman filter in positioning for autonomous vehicles, and its sensitivity to the process parameters

被引：13
|
作者：
Shoval, S [1 ]
Zeitoun, I [1 ]
Lenz, E [1 ]
机构：
[1] TECHNION ISRAEL INST TECHNOL,CTR ROBOT & MFG SYST,DEPT MECH ENGN,IL-32000 HAIFA,ISRAEL
来源：
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 1997年 / 13卷 / 10期
关键词：
AGV; Kalman filter; positioning; process parameters;
D O I：
10.1007/BF01179074
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Modern autonomous vehicles are using more than one method for performing the positioning task. The most common positioning methods for indoor vehicles are odometry for relative positioning and triangulation for absolute positioning. In many cases a Kalman filter is required to merge the data from the positioning systems and determines the vehicle position based on error analysis of the measurements and calculation procedures. A Kalman filter is particularly advantageous for ''on-the-fly'' positioning, which is performed while the vehicle is ita motion. This paper presents the implementation of a Kalman filter in ''ROBI'' - an AGV for material handling in a manufacturing environment. The performance of the filter in estimating the position of the AGV and the effect of motion parameters (speed, path curvature, beacon layout etc.) on filter accuracy are shown.
引用
收藏
页码：738 / 746
页数：9
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