摘要
为了既能正确地从视差图中检测出障碍,又能鲁棒地抵抗噪声的干扰,本文提出一种快速鲁棒的越野环境下自主移动机器人障碍检测算法.首先综合利用高度约束、连续性约束和坡度约束给出了障碍点的完整定义,然后借用区域增长的思想综合多种约束进行障碍检测,最后使用冗余检测方法与多分辨率策略对算法进行优化,并对冗余检测方法的原理进行证明.实验结果证明本文算法在各种不同的环境下都有效且鲁棒,算法的平均运行时间为25 ms,能够满足实时运行的要求.
In order to detect the obstacles from the disparity image correctly and resist the interference of the noise robustly,a fast and robust obstacle detection algorithm for off-road autonomous mobile robots is proposed.Firstly,a complete definition of obstacle point integrating the restrictions of height,continuity and slope is given,and then the idea of region growing is used to detect the obstacles with these restrictions.Finally,the algorithm is optimized by using the redundancy detection method and introducing the multi-dimensional strategy.In addition,the principle of the redundancy detection method is proved.Experiment results show that the algorithm is effective and robust in different environments.The average runtime of the algorithm is 25ms,which is fast enough for real time application.
出处
《机器人》
EI
CSCD
北大核心
2011年第3期287-291,298,共6页
Robot
基金
国家自然科学基金资助项目(90820302
90820015)
关键词
自主移动机器人
立体视觉
障碍检测
区域增长
autonomous mobile robot
stereo vision
obstacle detection
region growing
