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[1]鲁统伟,林芹,李熹,等.记忆运动方向的机器人避障算法[J].武汉工程大学学报,2013,(04):66-71.[doi:103969/jissn 16742869201304015]
 LU Tong wei,LIN Qin,LI Xi,et al.Obstacle avoidance algorithm of robot based on recording move direction[J].Journal of Wuhan Institute of Technology,2013,(04):66-71.[doi:103969/jissn 16742869201304015]
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记忆运动方向的机器人避障算法(/HTML)
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《武汉工程大学学报》[ISSN:1674-2869/CN:42-1779/TQ]

卷:
期数:
2013年04期
页码:
66-71
栏目:
机电与信息工程
出版日期:
2013-04-30

文章信息/Info

Title:
Obstacle avoidance algorithm of robot based on recording move direction
文章编号:
16742869(2013)04006606
作者:
鲁统伟1林芹1李熹2邹旭2
1.武汉工程大学计算机科学与工程学院,湖北 武汉 430074;2.智能机器人湖北省重点实验室,湖北 武汉 430074
Author(s):
LU Tongwei1LIN Qin1 LI Xi2ZOU Xu2
1. School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430074, China;2. Hubei Provience key Laburatory of Intelligenty Robot, Wuhan 430074, China
关键词:
Tangentbug避障运动方向仿真
Keywords:
Tangentbug obstacle avoidance movedirection simulation
分类号:
TP391.9
DOI:
103969/jissn 16742869201304015
文献标志码:
A
摘要:
在一般的避障环境中,Tangentbug算法表现的非常鲁棒,但当避障环境中有对称障碍物的时候,Tangentbug算法容易产生路径的死循环,从而导致终点不可到达.然而在机器人避障过程中,对称障碍物是非常常见的.针对这个问题,提出了基于记忆机器人运动方向的Tangentbug算法.该算法中,机器人每经过一个位置点,就把当前位置点和选择的运动方向记录下来,为后面的更新运动方向做好准备.首先,机器人扫描到障碍物时计算出机器人与障碍物的相遇方向;其次,根据障碍物的边缘,统计局部地图信息,得到局部切线图,找到离终点和当前点距离和最近的点作为机器人的下一个目标点,得到机器人的运动方向;然后,在机器人绕行障碍物时结合记忆的运动方向和局部切线图产生的最小距离和更新下一步运动方向.在整个避障过程中,不停的更新相遇方向和运动方向,最终实现机器人的直行和绕行,从而到达终点.通过大量实验验证,实验结果表明该算法不仅可以实现机器人在对称障碍物环境中顺利到达终点,也可以在非对称障碍物环境中达到终点,验证了该算法的有效性和鲁棒性.
Abstract:
Tangentbug algorithm performance is very robust in the general Obstacle Avoidance environment. When the Obstacle Avoidance environment has symmetrical obstacles, Tangentbug algorithm is prone to producing the infinite loop of path leading to the end point unreachable. However, the symmetrical obstacle is very common in the robot Obstacle Avoidance competition. The Tangentbug algorithm based on the memorizing moving direction was put forward. The robot recorded each passing by location point and corresponding moving direction for further updating direction of movement. Firstly, the direction between robot and obstacle was calculated when obstacle was scanned. Secondly, according to the edge of the obstacle, the statistics of local map information was got to find the nearest point to the end point and the local point as the next moving direction. Moreover, the moving direction was updated based on the minimum distance of the Local Tangent Graph and moving direction in memory when robot moved around the obstacle. The meet direction and the moving direction were updated in the entire process of obstacle avoidance. So that the robot would reach the end point by moving straight to the goal and moving around the obstacle. Experimental results show that the robot not only reaches the end point in a symmetrical obstacle environment, but also reaches the end point in the asymmetric obstacle environment, which verifies the effectiveness and robustness of the algorithm.

参考文献/References:

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备注/Memo

备注/Memo:
作者简介:鲁统伟(1979),男,山东莒南人,讲师,博士.研究方向:数字图像处理与智能系统.第35卷第4期2013年04月武汉工程大学学报JWuhanInstTechVol35No4Apr.2013
更新日期/Last Update: 2013-05-18