[1]陈庆强,汤龙梅,蔡文培.基于摄像头的智能车路径识别与方向控制算法[J].福建理工大学学报,2015,13(03):229-234.[doi:10.3969/j.issn.1672-4348.2015.03.005]
　Chen Qingqiang,Tang Longmei,Cai Wenpei.Camerabased path identification and steering control algorithm for smart vehicle[J].Journal of Fujian University of Technology;,2015,13(03):229-234.[doi:10.3969/j.issn.1672-4348.2015.03.005]
点击复制

基于摄像头的智能车路径识别与方向控制算法()
分享到：

《福建理工大学学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第13卷
期数:
2015年03期
页码:
229-234
栏目:
出版日期:
2015-06-25

文章信息/Info

Title:
Camerabased path identification and steering control algorithm for smart vehicle
作者:
陈庆强; 汤龙梅; 蔡文培
福建工程学院信息科学与工程学院
Author(s):
Chen Qingqiang;  Tang Longmei;  Cai Wenpei
College of Information Science and Engineering, Fujian University of Technology
关键词:
摄像头;  智能车;  路径识别;  方向控制
Keywords:
camera;  smart car;  path identification;  direction control
分类号:
TP336
DOI:
10.3969/j.issn.1672-4348.2015.03.005
文献标志码:
A
摘要:
针对A/D转换精度高但速度慢而电压比较器速度快但精度低，提出了结合二者来对摄像头输出的道路视频信息进行采集的方法。每行分别可靠采集12个高精度点和132个二值点，去噪后采用最小二乘法拟合直线获得智能车控制所需要的路径信息。采用跟踪智能车偏离引导线中心的平均距离和引导线斜率的双指标改进PID算法实现对智能车的方向控制。较传统的路径识别与方向控制算法相比，该算法具有数据采集和方向控制精确、系统鲁棒性更好的特点。实验结果验证了所提出方法的可行性。
Abstract:
A combined method of A/D conversion and voltage comparator was proposed to improve the precision and speed of road video data collection.12 highprecision point data and 132 binary data per row were achieved. The necessary path information for the smart vehicle to steer automatically was acquired by using linear least squares fitting method after denoising the data. An improved proportion, integration and differentiation (PID) algorithm was implemented to control the direction of the vehicle, considering both the average distance between the smart vehicle and the center of the guide line and the slope of the line. The proposed algorithm can acquire the path information and control the steer more accurately and is more robust compared with the traditional path recognition and steering control algorithm. The experimental results demonstrate the feasibility of the proposed method.

参考文献/References:

[1]薄亮亮，张小栋.光导AGV智能循迹测控系统的建模与仿真[J].测控技术,2011,30（5）：85-88,97.
[2]曾星星.基于摄像头的路径识别智能车控制系统设计[J].湖北汽车工业学院学报,2008，22(2):73-76.
[3]Minguez J, Montano L. Sensor based robot motion generation in unknown, dynamic and troublesome scenarios[J].Robotics and Autonomous Systems, 2005,52(4):290-311.
[4]Gonzalez Galvan E J, Cruz Ramirez S R, Seelinger M J,et al. An efficient multi camera, multi target scheme for the three dimensional control of robots using uncalibrated vision[J].Robotics and Computer Integrated Manufacturing,2003,19(5):387-400.
[5]Wasik Z, Saffiotti A. A fuzzy behaviollr based control system for manipulation [C]∥IEEE International Conference on Intelligent Robots and Systems，Sept.30-Oct.4 2002. New York: IEEE, 2002,2:1596-1601.
[6]卓晴,黄开胜,邵贝贝.学做智能车:挑战“飞思卡尔”杯[M].北京:北京航空航天大学出版社,2007.
[7]王明顺,沈谋全.传感器与智能车路径识别[J]. 电子产品设计，2007，4（1）：142-143.
[8]刘建刚,程磊,黄剑,等.基于CCD图像识别的HCS12单片机智能车控制系统[J].光电技术应用,2007,22（6）：52-55，59.
[9]程亚龙,周怡君. 基于CMOS传感器的智能车路径识别研究[J].机械制造与研究,2007,36(5):13-15.
[10]曾军.基于MC9S12DG128单片机的智能寻迹车设计[J].电子设计工程,2009,17(3):54-56.
[11]刘博,张盛兵,马志强. 基于最优路径的智能车设计与实现[J]. 计算机测量与控制,2012, 20(8):2264-2269.
[12]韩毅,杨天.基于HCS12单片机的智能寻迹模型车的设计与实现[J].计算机工程与设计,2008,29(18):4736-4739.
[13]李国柱.基于CMOS摄像头的智能车路径跟踪系统设计[J]. 现代电子技术,2011,34(18):12-14,17.

更新日期/Last Update: 2015-06-25