A path planning algorithm of intelligent transportation robot based on extended Kalman filter

Guan He, Honglan Yang
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引用次数: 0

Abstract

Aiming at the problem of long calculation time and slow response speed of traditional intelligent transportation robot path planning algorithm, an intelligent transportation robot path planning algorithm based on extended Kalman filter is proposed. By analysing the relevant principles of optical flow localisation, aiming at the fact that a single optical flow sensor can not meet the needs of all application scenarios, multiple optical flow sensors are fused through extended Kalman filter, and the system model and observation model of intelligent transportation robot are established at the same time. The optical flow sensor is fixed on the intelligent transportation robot, the two-dimensional coordinates of the intelligent transportation robot are obtained in real time, and the moving path is planned. The results show that the proposed algorithm can reduce the operation time and improve the response efficiency.
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基于扩展卡尔曼滤波的智能交通机器人路径规划算法
针对传统智能交通机器人路径规划算法计算时间长、响应速度慢的问题,提出了一种基于扩展卡尔曼滤波的智能交通机器人路径规划算法。通过分析光流定位的相关原理,针对单个光流传感器无法满足所有应用场景的需求,通过扩展卡尔曼滤波将多个光流传感器融合,同时建立智能交通机器人的系统模型和观测模型。将光流量传感器固定在智能运输机器人上,实时获取智能运输机器人的二维坐标,并规划其移动路径。实验结果表明,该算法能有效地缩短操作时间,提高响应效率。
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来源期刊
International Journal of Manufacturing Technology and Management
International Journal of Manufacturing Technology and Management Engineering-Industrial and Manufacturing Engineering
CiteScore
0.70
自引率
0.00%
发文量
6
期刊介绍: IJMTM is a refereed and authoritative source of information in the field of manufacturing technology and management and related areas.
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