主管:中华人民共和国应急管理部
主办:应急管理部天津消防研究所
ISSN 1009-0029  CN 12-1311/TU

消防科学与技术 ›› 2024, Vol. 43 ›› Issue (1): 96-99.

• • 上一篇    下一篇

基于工业物联网多感知技术的消防巡检机器人研究

朱荣飞   

  1. (上海市徐汇区消防救援支队,上海 200232)
  • 出版日期:2024-01-15 发布日期:2024-01-15
  • 作者简介:朱荣飞(1986- ),上海人,上海市徐汇区消防救援支队防火监督一科科长,工程师,主要从事消防监督管理方面的研究,上海市徐汇区武宣路150号,200232。

Research on fire inspection robot based on industrial internet of things multi perception technology

Zhu Rongfei   

  1. (Shanghai Xuhui Fire and Rescue Division, Shanghai 200232, China)
  • Online:2024-01-15 Published:2024-01-15

摘要: 针对现有消防机器人路径规划蚁群算法全局搜索能力弱、收敛速度慢、易陷入局部最优的难题,提出了一种基于回滚和正反向优化策略的蚁群路径规划算法。它通过改进全局初始化信息,采用回滚策略和蚁群正反向优化方法,提升全局搜索能力和速度。基于MATLAB和ROS的仿真结果表明:本文提出的改进蚁群算法提高了收敛性,减少了迭代次数,缩短了巡逻路径长度,为消防机器人火场救援节省宝贵的时间。

关键词: 消防机器人, 路径规划, 蚁群算法, 回滚策略, 正反向优化

Abstract: In response to the challenges of weak global search ability, slow convergence speed, and easy falling into local optima in existing ant colony algorithms for path planning of fire robots, an ant colony path planning algorithm based on rollback and forward and backward optimization strategies is proposed. It enhances global search capability and speed by improving global initialization information, adopting rollback strategies and ant colony forward and backward optimization methods. The simulation results based on MATLAB and ROS show that the improved ant colony algorithm proposed in this paper improves convergence, reduces iteration times, shortens patrol path length, and saves valuable time for firefighting robot fire rescue.

Key words: firefighting robot, path planning, ant colony algorithm, rollback strategy, forward and backward optimization