Multi-sensor fusion technology based tracking car

被引:0
|
作者
Chen Chao-Da [1 ,2 ]
Li Ying-Qiong [1 ]
Zhong Li-Hua [1 ]
机构
[1] Guangdong Polytech Normal Univ, Tianhe Coll, Guangzhou, Guangdong, Peoples R China
[2] Guangdong Univ Technol, Guangzhou, Guangdong, Peoples R China
关键词
Single chip microcomputer; Infrared tube; Photoelectric sensor;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Multi sensor fusion technology of vehicle tracking is a set of environment perception, planning and decision-making, auxiliary driving level functions in an integrated system and is an important part of the intelligent transportation system. It has wide application prospects in military, civil, space development and other fields. The design of multi sensor fusion technology of vehicle tracking control system is researched, designed and implemented based on path planning of intelligent vehicle control system. At present, such devices have been applied to many aspects, such as archaeology, robots, entertainment and so on. Multi sensor fusion technology vehicle tracking is an important part of mobile robot, the design by real-time detection of each module of the sensor input signal using infrared to detect black line to achieve obstacle avoidance, through photoelectric sensors tracking the storage space larger as the main control chip, driving motor car used L298N chip, achieve automatic identification trolley line, the more effective control of the in run into obstacles can driving steering angle and tracking.
引用
下载
收藏
页码:1106 / 1109
页数:4
相关论文
共 50 条
  • [41] Multi-sensor fusion for real-time object tracking
    Verma, Sakshi
    Singh, Vishal K. K.
    MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (07) : 19563 - 19585
  • [42] Adaptive Fingerprinting in Multi-Sensor Fusion for Accurate Indoor Tracking
    Belmonte-Hernandez, Alberto
    Hernandez-Penaloza, Gustavo
    Alvarez, Federico
    Conti, Giuseppe
    IEEE SENSORS JOURNAL, 2017, 17 (15) : 4983 - 4998
  • [43] A novel distributed fusion algorithm for multi-sensor nonlinear tracking
    Liu, Jingxian
    Wang, Zulin
    Xu, Mai
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2016,
  • [44] A new adaptive weighted fusion algorithm for multi-sensor tracking
    Zhao, J
    Hu, SQ
    2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS, 2002, : 285 - 287
  • [45] Cooperative Tracking Technology of Single Target Multi-Sensor Based on Cooperative Index
    Gong, Jian-Wen
    Wang, Xiao-Feng
    Yang, Ri-Jie
    MOBILE NETWORKS & APPLICATIONS, 2020, 25 (04): : 1594 - 1603
  • [46] CurbScan: Curb Detection and Tracking Using Multi-Sensor Fusion
    Baek, Iljoo
    Tai, Tzu-Chieh
    Bhat, Manoj Mohan
    Ellango, Karun
    Shah, Tarang
    Fuseini, Kamal
    Rajkumar, Ragunathan
    2020 IEEE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2020,
  • [47] A novel distributed fusion algorithm for multi-sensor nonlinear tracking
    Jingxian Liu
    Zulin Wang
    Mai Xu
    EURASIP Journal on Advances in Signal Processing, 2016
  • [48] Multi-sensor fusion for real-time object tracking
    Sakshi Verma
    Vishal K. Singh
    Multimedia Tools and Applications, 2024, 83 : 19563 - 19585
  • [49] An evaluation of several fusion algorithms for multi-sensor tracking system
    Liu, Zhi
    Wang, Minghui
    Huang, Jiangtao
    Journal of Information and Computational Science, 2010, 7 (10): : 2101 - 2109
  • [50] Multi-sensor data fusion for optical tracking of head pose
    Luo B.
    Wang Y.-T.
    Liu Y.
    Zidonghua Xuebao/Acta Automatica Sinica, 2010, 36 (09): : 1239 - 1249