The algorithm of autonomous obstacle avoidance based on behavior fusion for mobile robot

BAO Qing-yong1; LI Shun-ming1; SHEN Huan1; SHANG Wei-yan2

doi:10.13873/j.1000-97872010.05.027

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The algorithm of autonomous obstacle avoidance based on behavior fusion for mobile robot

更新时间：2025-09-11

- The algorithm of autonomous obstacle avoidance based on behavior fusion for mobile robot
- Vol. 29, Issue 5, Pages: 70-73+76(2010)
- 作者机构：
  
  1. 南京航空航天大学能源与动力学院
  2. 宁波工程学院机械工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872010.05.027
  CLC： TP242
- Published：2010
- 稿件说明：
移动端阅览
[1]鲍庆勇,李舜酩,沈峘,尚伟燕.基于行为融合的移动机器人自主避障算法[J].传感器与微系统,2010,29(05):70-73+76.

BAO Qing-yong1, LI Shun-ming1, SHEN Huan1, et al. The algorithm of autonomous obstacle avoidance based on behavior fusion for mobile robot[J]. 2010, 29(5): 70-73+76.
[1]鲍庆勇,李舜酩,沈峘,尚伟燕.基于行为融合的移动机器人自主避障算法[J].传感器与微系统,2010,29(05):70-73+76. DOI： 10.13873/j.1000-97872010.05.027.

BAO Qing-yong1, LI Shun-ming1, SHEN Huan1, et al. The algorithm of autonomous obstacle avoidance based on behavior fusion for mobile robot[J]. 2010, 29(5): 70-73+76. DOI： 10.13873/j.1000-97872010.05.027.

摘要

当移动机器人面临环境未知或不确定时

各个行为融合的权重随环境的变化而变化

从而导致权重无法在线调整而不能顺利到达目标点。为此

提出一种权重可在线调整的自主避障行为融合算法。用Mamdani型模糊控制器设计移动机器人自主避障过程中的基本行为;同时

提出一种基于两级BP神经网络信息融合的权重调整方法来实现各个基本行为的融合。该算法能够根据环境的变化实现各个基本行为权重的在线调整

增强自主避障控制的实时性和鲁棒性。仿真实验结果表明了该算法的有效性和可行性。

Abstract

When the mobile robot facing unknown or uncertain environment

the weight of each behavior changes along with the environment change

resulting in that the weight can not adjust online

so the mobile robot can not arrive target point successfully.An autonomous obstacle avoidance behavior fusion algorithm that the weight can adjust online is presented.Mamdani type fuzzy controller is used to design basic behaviors in autonomous obstacle avoidance process for mobile robot.At the same time

a new method of weight adjustment based on two-stage BP neural network information fusion is presented to realize each basic behavior fusion to determine the weight of each behavior based on to fuse each behavior.This algorithm can realize online adjustment of each basic behavior weight according to environmental change and can strengthen real-timing and robustness of the autonomous obstacle avoidance control.The experiment results indicate that the algorithm is effective and feasible.

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references

自主移动机器人局部路径规划综述 [J]. 鲍庆勇,李舜酩,沈峘,门秀花. 传感器与微系统 . 2009(09)

在未知环境下基于递阶模糊行为的移动机器人控制算法 [J]. 李寿涛,李元春. 吉林大学学报(工学版) . 2005(04)

神经网络理论及其工程应用[M]. 测绘出版社 , 胡伍生, 2006

A Novel Navigation Method for Autonomous Mobile Vehicles [J] . Cang Ye,Danwei Wang. Journal of Intelligent and Robotic Systems . 2001 (4)

Real-time Collision-free Path Planning of Robot Manipulators using Neural Network Approaches [J] . Simon X. Yang,Max Meng. Autonomous Robots . 2000 (1)

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