Autonomous navigation of intelligent electric vehicle of multi-sensor data fusion

YE Mei-song; XIAO Shi-de; ZHANG Zhi-feng; ZHAO Yang; WANG Hong-yan

doi:10.13873/j.1000-9787(2017)09-0084-04

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Autonomous navigation of intelligent electric vehicle of multi-sensor data fusion

更新时间：2025-09-11

- Autonomous navigation of intelligent electric vehicle of multi-sensor data fusion
- Vol. 36, Issue 9, Pages: 84-87(2017)
- 作者机构：
  
  西南交通大学机械工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-9787(2017)09-0084-04
  CLC： TP212;TP242.6
- Published：2017
- 稿件说明：
移动端阅览
[1]叶美松,肖世德,张志峰,赵阳,王鸿雁.多传感器数据融合的智能电动车自主导航[J].传感器与微系统,2017,36(09):84-87.

YE Mei-song, XIAO Shi-de, ZHANG Zhi-feng, et al. Autonomous navigation of intelligent electric vehicle of multi-sensor data fusion[J]. 2017, 36(9): 84-87.
[1]叶美松,肖世德,张志峰,赵阳,王鸿雁.多传感器数据融合的智能电动车自主导航[J].传感器与微系统,2017,36(09):84-87. DOI： 10.13873/j.1000-9787(2017)09-0084-04.

YE Mei-song, XIAO Shi-de, ZHANG Zhi-feng, et al. Autonomous navigation of intelligent electric vehicle of multi-sensor data fusion[J]. 2017, 36(9): 84-87. DOI： 10.13873/j.1000-9787(2017)09-0084-04.

摘要

以四轮驱动电动车为研究对象

将智能电动车上多种传感器所采集的信息进行处理与融合

实现校园环境里的自主行驶与导航。提出了在空旷路段和沿墙导航的控制决策

着重研究了沿墙算法和入弯算法

使智能电动车在不同的环境下可以有效地完成自主导航。实验结果表明:该导航控制策略和算法具有较高的可靠性。

Abstract

Four-wheel drive electric vehicle is research target. The information collected by a variety of sensors in smart car is processed and integrated

the purpose is to complete autonomous travel and navigation in campus environment. Navigation control decision-making in open sections and along wall is put forward

along wall algorithm and bending algorithm is focused on

intelligent electric vehicle can effectively achieve autonomous navigation in different environments. The experimental results show that the navigation control strategy and algorithm have high reliability.

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references

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城市环境下无人驾驶车辆决策系统研究 [D]. 陈佳佳. 中国科学技术大学 2014

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