A Heuristic Path Planning Algorithm for Inspection Robots

被引:0
作者
Tang, Qichao [1 ]
Ma, Lei [1 ]
Sun, Yongkui [1 ]
Yang, Guang [1 ]
Li, Zhongfa [1 ]
Zhao, Duo [1 ]
机构
[1] Southwest Jiaotong Univ, Sch Elect Engn, Chengdu 611756, Peoples R China
来源
PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE | 2020年
关键词
Traction substation inspection robot; path planning; optimization problem; cross-entropy optimization algorithm;
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
In this paper a novel heuristic path planning algorithm based on cross-entropy optimization is proposed for substation inspection robots. We seek to provide a low-cost, fast and effective solution for such robots. The optimization problem is modeled based on a topology map of the substation, it turns out to be non-convex yet requires real-time solution. A classification algorithm is applied to simplify the task points to reduce the computational cost and to speed up the path planning. The cross-entropy optimization algorithm is used to derive the shortest path among the simplified task points. Then, a path resolution algorithm is implemented to resolve the simplified path to the original task space and eventually get the real inspection path. Simulative and experimental studies have verified feasibility and effectiveness of the proposed method. Particularly, the algorithm implemented on an embedded computer delivers a solution for 153 task points in only three seconds, while very low repetition rate (about 0.2%) is approached.
引用
收藏
页码:3834 / 3839
页数:6
相关论文
共 50 条
  • [21] Flexible Inspection Path Planning Based on Adaptive Genetic Algorithm
    Yang Zeqing
    Liu Libing
    Yang Weidong
    2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11, 2008, : 1558 - 1563
  • [22] Application of Adaptive Genetic Algorithm in Flexible Inspection Path Planning
    Yang Zeqing
    Liu Libing
    Tan Zhihong
    Liu Weiling
    PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 5, 2008, : 75 - +
  • [23] Path planning for mobile articulated robots based on the improved A* algorithm
    Xu, Yaru
    Liu, Rong
    INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2017, 14 (04): : 1 - 10
  • [24] Detecting Robots Path Planning Based on Improved Genetic Algorithm
    Cui, Shi-Gang
    Dong, Jiang-Lei
    2013 THIRD INTERNATIONAL CONFERENCE ON INSTRUMENTATION & MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC), 2013, : 204 - 207
  • [25] Bacterial memetic algorithm for offline path planning of mobile robots
    Botzheim, Janos
    Toda, Yuichiro
    Kubota, Naoyuki
    MEMETIC COMPUTING, 2012, 4 (01) : 73 - 86
  • [26] Path Planning of Underwater Swarm Robots using Genetic Algorithm
    Vicmudo, Marck P.
    Dadios, Elmer P.
    Vicerra, Ryan Rhay P.
    2014 INTERNATIONAL CONFERENCE ON HUMANOID, NANOTECHNOLOGY, INFORMATION TECHNOLOGY, COMMUNICATION AND CONTROL, ENVIRONMENT AND MANAGEMENT (HNICEM), 2014,
  • [27] Path Planning of Intelligent Mobile Robots with an Improved RRT Algorithm
    Zhu, Wenliang
    Qiu, Guanming
    APPLIED SCIENCES-BASEL, 2025, 15 (06):
  • [28] Bacterial memetic algorithm for offline path planning of mobile robots
    János Botzheim
    Yuichiro Toda
    Naoyuki Kubota
    Memetic Computing, 2012, 4 : 73 - 86
  • [29] A Novel Algorithm for Path Planning of Mobile Robots in Dynamic Environment
    Ning, Xiaomei
    Ma, Zhanchun
    Guo, Li
    SMART MATERIALS AND NANOTECHNOLOGY IN ENGINEERING, 2012, 345 : 370 - +
  • [30] Path Planning for Mobile Robots based on Visibility Graphs and A* Algorithm
    Contreras, Juan D.
    Fernando Martinez, S.
    Martinez, Fredy H. S.
    SEVENTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2015), 2015, 9631