[1]贾丙佳,李平.邻近障碍物整体化的机器人路径规划[J].华侨大学学报(自然科学版),2019,40(6):799-805.[doi:10.11830/ISSN.1000-5013.201903010]
　JIA Bingjia,LI Ping.Robot Path Planning With Integration of Neighbouring Obstacles[J].Journal of Huaqiao University(Natural Science),2019,40(6):799-805.[doi:10.11830/ISSN.1000-5013.201903010]
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邻近障碍物整体化的机器人路径规划()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第40卷
期数:
2019年第6期
页码:
799-805
栏目:
出版日期:
2019-11-20

文章信息/Info

Title:
Robot Path Planning With Integration of Neighbouring Obstacles
文章编号:
1000-5013(2019)06-0799-07
作者:
贾丙佳;  李平
华侨大学 信息科学与工程学院, 福建 厦门 361021
Author(s):
JIA Bingjia;  LI Ping
College of Information Science and Engineering, Huaqiao University, Xiamen 361021, China
关键词:
自主移动机器人;  路径规划;  邻近障碍物整体化;  人工势场法;  局部极小值
Keywords:
autonomous mobile robot;  route plan;  integration of neighbouring obstacles;  artificial potential field method;  local minimum point
分类号:
TP242.6
DOI:
10.11830/ISSN.1000-5013.201903010
文献标志码:
A
摘要:
针对采用传统的人工势场法进行路径规划时,在障碍物密集分布的区域容易使机器人陷入其中,导致停止不前或循环往复,出现局部极小值的问题,提出一种密集邻近障碍物整体化的机器人路径规划方法.首先,通过传感器检测障碍物的位置信息,根据相邻障碍物之间的距离划分密集分布的障碍物区域;然后,以该区域的中心为圆心,确定一个外接圆,对障碍物进行整体化处理;最后,用整体化障碍物替代原先的多个障碍物.在MATLAB软件平台上,对文中方法进行仿真.结果表明:与传统人工势场法相比,文中方法可以有效避开局部极小值,顺利完成路径规划任务;与增设引导点的方法相比,文中方法可有效减少机器人从起始位置到达目标位置的时间,提高路径规划的效率.
Abstract:
In order to solve the problem that the robot is easily trapped in the area where obstacles are densely distributed in the traditional artificial potential field method for path planning, stopping or reciprocating, leading to local minimum, a robot path planning method of integrating densely adjacent obstacles is proposed. Firstly, the location of obstacles is detected by sensors. According to the distance between adjacent obstacles, the densely distributed obstacle areas are divided; then, taking the center of the area as the circle center, a circumscribed circle is determined, and the obstacles are treated as a whole; finally, the integral obstacles are used to replace the original obstacles. On the MATLAB software platform, the proposed method is simulated. The results show that compared with the traditional artificial potential field method, the proposed method can effectively avoid the local minimum and successfully complete the path planning task. Compared with the method of adding guidance points, the proposed method can effectively reduce the time from the initial position to the target and improve the efficiency of path planning.

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备注/Memo

备注/Memo:
收稿日期: 2019-03-05
通信作者: 李平(1981-),女,副教授,博士,主要从事非线性系统与智能控制、复杂控制系统的研究.E-mail:pingping_1213@126.com.
基金项目: 国家自然科学基金资助项目(61603144); 福建省自然科学基金资助项目(2018J01095); 福建省高校产学合作科技重大项目(2013H6016); 华侨大学中青年教师科技创新资助计划项目(ZQN-PY509)
更新日期/Last Update: 2019-11-20