计算机应用 ›› 2019, Vol. 39 ›› Issue (9): 2523-2528.DOI: 10.11772/j.issn.1001-9081.2019020317

• 人工智能 • 上一篇    下一篇

基于改进模糊算法的水面无人艇自主避障

林政, 吕霞付   

  1. 重庆邮电大学 自动化学院, 重庆 400065
  • 收稿日期:2019-02-26 修回日期:2019-04-24 发布日期:2019-05-14 出版日期:2019-09-10
  • 通讯作者: 林政
  • 作者简介:林政(1995-),男,四川富顺人,硕士研究生,主要研究方向:嵌入式开发、智能机器人;吕霞付(1966-),男,安徽六安人,教授,博士,主要研究方向:仪器仪表、汽车电子。
  • 基金资助:

    国家自然科学基金资助项目(61275077)。

Autonomous obstacle avoidance of unmanned surface vessel based on improved fuzzy algorithm

LIN Zheng, LYU Xiafu   

  1. College of Automation, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
  • Received:2019-02-26 Revised:2019-04-24 Online:2019-05-14 Published:2019-09-10
  • Supported by:

    This work is partially supported by the National Natural Science Foundation of China (61275077).

摘要:

为了提高水面无人艇(USV)在未知、复杂环境下的连续避障性能,提出一种具有速度反馈的模糊避障算法。USV利用激光扫描雷达与多路超声波传感器感知周围环境,通过对障碍物信息进行分组并设置权值的方式进行多传感器数据融合,并在模糊控制的基础上根据环境情况自动调整航速;进而提出一种考虑障碍物所有分布情况的更全面的模糊控制规则表,增强了USV对复杂环境的适应能力。实验结果表明,所提方法能通过与环境交互调整USV航速使其成功避障并优化避障路径,具有良好的可行性和有效性。

关键词: 水面无人艇, 避障, 数据融合, 模糊控制, 速度反馈

Abstract:

In order to improve the performance of continuous obstacle avoidance ability of Unmanned Surface Vessel (USV) in unknown and complex environment, a fuzzy algorithm of obstacle avoidance with speed feedback was proposed. The USV utilized laser scanning radar and multi-channel ultrasonic sensors to perceive the surroundings and performed multi-sensor data fusion by grouping and setting the weight of the obstacle information, and the speed of USV was automatically adjusted according to the environmental situation based on fuzzy control. Then a more comprehensive fuzzy control rule table considering all the distribution of obstacles was proposed to enhance the adaptability of USV to complex environments. The experimental results show that the algorithm can make the USV successfully avoid obstacles and optimize the obstacle avoidance path by adjusting the speed through interaction with the environment, and has good feasibility and effectiveness.

Key words: unmanned surface vessel, obstacle avoidance, data fusion, fuzzy control, speed feedback

中图分类号: