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本科基于人工势场法的机器人路径规划.doc
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摘要
路径规划是移动机器人研究的一个基本而又极其重要的课题。灵活有效
的路划算法能够帮助机器人适应各种复杂的环境。本文针对移动机器人在已
知环境下的路径规划作了下列工作:
回顾了现有算法,如几何法,栅格法,人工势场法。对人工势场法作了
深入的探讨。本文详细的探讨了这一问题,并且通过仿真来说明方法的有效
性。在己知环境下通过仿真检验说明人工势场法的优点:避障算法简单,实
时性好,但是当障碍物距目标点很近时,人工势场法在使机器人到达目标点
上却有着一些固有的缺点和局限性。
提出了改进的势场法,改进的势场法可以克服势场法的上述缺点,并通
过仿真实验说明了改进方法的有效性。
关键字:移动机器人 路径规划 人工势场法
Abstract
Path planning is a fundamental issue in the mobile robot research. Flexible
and effective path planning algorithm is helpful for the robot to adapt to a
complex environment. Considering the path planning of a mobile robot in an
known environment, this paper does the following work.
1) The existing algorithms are reviewed, such as Geometry Vertex, Grid,
Artificial Potential Field and etc. . The artificial potential field is studied. The
paper discusses this method in detail. Simulation is done to illustrate the effect of
strategy. For a known environment, some simulation is done to show the pros
of artificial potential field. The algorithm is simple, real-time. But there are some
inherent flaws and limitations in object reaching when an obstacle is closed to
the object.
An improved potential field is proposed to overcome shortcomings
mentioned above. Simulation is done to show the effectiveness of the proposed
method.
Keyword:mobile robot , path planning, artificial potential field
目 录
第 1 章 前
言································································································
········1
1.1 机器人概
述···························································································1
1.2 移动机器人概
述···················································································1
1.3 路径规划的概念和意
义·······································································2
第 2 章 人工势场
法····························································································6
2.1 场强的基本模
型···················································································6
2.2 人工势场模
型·······················································································7
2.3 移动机器人的受力分
析·······································································8
2.4 基于人工势场的移动机器人路径规划步
骤·····································10
2.5 仿真实
验······························································································
10
2.5.1 不同障碍物密度下的规划结
果···················································10
2.5.2 不同
k
,
η
对规划结果的影
响······················································14
2.6 本章小
节······························································································
17
第 3 章 基于改进的人工势场的移动机器人路径规
划···································18
3.1 引
言································································································
····18
3.2 势场模型存在的缺
陷·······································································19
3.3 势场模型的改
进················································································21
3.4 不可到达问题的解
决········································································23
3.5 动态环境下的路径规
划····································································26
3.6 本章小
节····························································································2
6
第 4 章 总
结································································································
·······27
致
谢································································································
···················28
参考文
献································································································
···········29
附
录································································································
···················30
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