The Research of Multi-Layer-Based on Path Planning for Generating Optimal Path

被引:0
|
作者
Sa, Jiwon [1 ]
Lim, Kyungil [1 ]
Kim, Jungha [1 ]
机构
[1] Kookmin Univ, Kookmin Unmanned Vehicle Res Lab, Seoul 136702, South Korea
关键词
Under Layer Path Planner; Upper Layer Path Planner; Arbiter; Path Update;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this Paper, to provide the Multi-Layer Based on Path Planning System(MLPPS) for generated optimal path. Previously used path planning system, single-layer based on path planning system, local map of the path in a single situation was ensured by the optimal path. However, there is a problem that continuously local map is acquired to update the more than necessary parts of the map. These problem are due to the continuous path update, can maintain the unnecessary paths, so that it is impossible to ensure optimal path planning system. To solve this problem, we propose MLPPS. Unlike single layer path planning system, MLPPS was divided Under Layer Path Planner and Upper Layer Path Planner. Under Layer Path Planner is generated the local path. And Upper Layer Path Planner is transmitted the optimal path to autonomous vehicle. The Arbiter is present between the two layers. Arbiter through the decision-making local path of the Under Layer Path Planner is to determine whether the optimal path. In the remainder of this paper, it describes how to generate local paths by Under Layer Path Planner and optimal path determined by Arbiter.
引用
收藏
页码:896 / 899
页数:4
相关论文
共 50 条
  • [41] NURBS Based Multi-objective Path Planning
    Jalel, Sawssen
    Marthon, Philippe
    Hamouda, Atef
    PATTERN RECOGNITION (MCPR 2015), 2015, 9116 : 190 - 199
  • [42] Research on Path Planning of Manipulator
    Wang, Nana
    Peng, Yizhun
    Yang, Zhou
    Zhang, Yuheng
    PROCEEDINGS OF THE 2021 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS (ICAROB 2021), 2021, : 559 - 564
  • [43] AN OPTIMAL PATH PLANNING PROBLEM FOR HETEROGENEOUS MULTI-VEHICLE SYSTEMS
    Klauco, Martin
    Blazek, Slavomir
    Kvasnica, Michal
    INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE, 2016, 26 (02) : 297 - 308
  • [44] Research on Path-planning of Manipulator based on Multi-agent Reinforcement Learning
    Tong, Liang
    FRONTIERS OF MANUFACTURING AND DESIGN SCIENCE, PTS 1-4, 2011, 44-47 : 2116 - 2120
  • [45] Optimal Multi-Robot Path Planning with Temporal Logic Constraints
    Ulusoy, Alphan
    Smith, Stephen L.
    Ding, Xu Chu
    Belta, Calin
    Rus, Daniela
    2011 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, 2011, : 3087 - 3092
  • [46] Optimal Multi-Agent Map Coverage Path Planning Algorithm
    Zheng, Yangxing
    Tu, Xiaowei
    Yang, Qinghua
    2020 CHINESE AUTOMATION CONGRESS (CAC 2020), 2020, : 6055 - 6060
  • [47] A multi-agent optimal path planning approach to robotics environment
    Kumar T., Gireesh
    Vijayan, Vinodh. P.
    ICCIMA 2007: INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND MULTIMEDIA APPLICATIONS, VOL I, PROCEEDINGS, 2007, : 400 - 404
  • [48] Research and development trend of multi-UAV path planning based on metaheuristic algorithm
    Zhao C.
    Liu Y.-G.
    Chen L.
    Li F.-Z.
    Man Y.-C.
    Kongzhi yu Juece/Control and Decision, 2022, 37 (05): : 1102 - 1115
  • [49] Cellular automata and optimal path planning
    Stampfle, M
    INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 1996, 6 (03): : 603 - 610
  • [50] Voronoi diagram in optimal path planning
    Bhattacharya, Priyadarshi
    Gavrilova, Marina L.
    ISVD 2007: THE 4TH INTERNATIONAL SYMPOSIUM ON VORONOI DIAGRAMS IN SCIENCE AND ENGINEERING 2007, PROCEEDINGS, 2007, : 38 - +