上海交通大学学报

上海交通大学学报（自然版） ›› 2012, Vol. 46 ›› Issue (02): 213-216.

• 自动化技术、计算机技术 • 上一篇    下一篇

基于多目标优化的移动机器人避障算法    

杨晶东1，杨敬辉2，蔡则苏3   

  1. （1.上海理工大学 光电信息与计算机工程学院，上海 200093；2.上海第二工业大学 经济与管理学院，上海 201209；3.哈尔滨工业大学 计算机科学与技术学院，哈尔滨 150001）
  • 收稿日期:2011-08-31 出版日期:2012-02-28 发布日期:2012-02-28
  • 基金资助:

    国家自然科学基金资助项目（60874002），上海理工大学教师创新基金建设项目(GDCXT1101)

Obstacle Avoidance Based on Multiple Objective Optimization for Mobile Robots

 YANG  Jing-Dong-1, YANG  Jing-Hui-2, CAI  Ze-Su-3   

  1. (1. School of OpticalElectrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China; 2. School of Business Management, Shanghai Second Polytechnic University, Shanghai 201209, China; 3. School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China)
  • Received:2011-08-31 Online:2012-02-28 Published:2012-02-28

摘要： 针对移动机器人自主导航过程中由于过多寻求当前时刻最优路径或最优解而产生死锁或震荡现象，提出了一种动态变化权重的移动机器人行为融合避障算法.该算法利用多目标优化方法获得移动机器人最有效解，并把指定目标的移动机器人避障导航过程分解为3个子行为避障系统.通过动态改变子行为函数的权重和优先级，实时获得当前时刻最满意路径或最有效路径.实验结果表明，该算法可在确保避障过程鲁棒性前提下，有效地改善避障导航的安全性和平滑性。

关键词: 多目标优化, 模糊行为融合, 死锁, 避障平滑性

Abstract: Obstacle avoidance is an important aspect of navigation for autonomous mobile robots. An efficient algorithm of obstacle avoidance was put forward based on multiple objective optimization (MOO) theory. The algorithm gives how to acquire the efficient solution for mobile robots using the multiple objective optimization theory. The method divides the navigation with the given goal into three subbehaviors, which can be changed dynamically according to the current weighting or priority, in order to acquire the most satisfying path or preferred solution at current time. In the end, the experiment shows that the algorithm can improve the security and smoothness of obstacle avoidance efficiently without sacrificing the
robustness of the whole process.

Key words: multiple objective optimization, behavior fusion, deadlock, smoothness of obstacle avoidance

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