Open AccessPath Planning for Construction Machinery Based on Improved Potential Field Ant Colony Algorithm
Author(s) -
Peigang Li,
Pengcheng Li,
Yining Xie,
Xiaoyi Feng,
Bin Hu,
Congfeng Tian,
Ruwei Zhang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2095/1/012062
Subject(s) - ant colony optimization algorithms , heuristic , algorithm , raster graphics , computer science , convergence (economics) , field (mathematics) , motion planning , mathematical optimization , path (computing) , ant colony , selection (genetic algorithm) , potential field , artificial intelligence , mathematics , robot , geophysics , geology , pure mathematics , economics , programming language , economic growth
The path planning algorithm of unmanned construction machinery is studied, and the potential field ant colony algorithm is improved to be applied in the field of unmanned construction machinery. Firstly, the raster map modeling was optimized to eliminate the trap grid in the map. At the beginning of algorithm iteration, the heuristic information of artificial potential field method was added and the global pheromone updating model was improve the convergence speed of the algorithm. In addition, the weight coefficient of potential field force and local pheromone updating model were introduced to enhance the development of raster map in the later iteration of ant colony algorithm and reduce the influence of heuristic information of potential field force. Finally, the selection range of parameters such as optimal pheromone heuristic factor and ant colony number is determined by simulation, and it is verified that the algorithm is better than the basic ant colony algorithm.