广东工业大学学报 ›› 2016, Vol. 33 ›› Issue (05): 9-14.doi: 10.3969/j.issn.1007-7162.2016.05.003

• 综合研究 • 上一篇    下一篇

自主移动机器人走廊识别算法研究与改进

曾碧, 林展鹏, 邓杰航   

  1. 广东工业大学 计算机学院,广东 广州 510006
  • 收稿日期:2015-03-02 出版日期:2016-09-10 发布日期:2016-09-10
  • 作者简介:曾碧(1963-),女,教授,博士,主要研究方向为智能机器人、嵌入式智能计算.
  • 基金资助:

    国家自然科学基金资助项目(61202267);广东省产学研合作专项资助项目(2014B090904080)

Algorithm Research on Recognition and Improvement for Corridor of Autonomous Mobile Robot

Zeng Bi, Lin Zhan-peng, Deng Jie-hang   

  1. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2015-03-02 Online:2016-09-10 Published:2016-09-10

摘要:

针对移动机器人在室内环境下自主导航过程中的走廊识别问题,提出一种改进的走廊识别算法.该算法采用由Kinect传感器提供的深度图信息,利用连续点间的深度差值和最小二乘法拟合直线检测走廊出口存在性,最后结合贝叶斯分类器完成对走廊类别的判定.实验表明,该方法能够高效地识别走廊类型,同时具有较好的鲁棒性,并且在复杂的室内环境下依然能够保持较高的走廊类型识别率.

关键词: 走廊识别; 深度图; 差值; 最小二乘法; Kinect

Abstract:

For the problem of corridor recognition for autonomous mobile robot in the process of navigation in the indoor environment, an improved corridor recognition algorithm is proposed. The algorithm uses information of depth image provided by kinect sensor, and the depth difference between consecutive points and least squares are used to fit a straight line to detect the existence of corridor outlet. Experimental results show that the algorithm can efficiently recognize corridor types while having a robust, and is still able to maintain a high recognition rate of corridor types in a complex indoor environment.

Key words: corridor recognition; depth image; difference; least squares; Kinect

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