基于Kinect深度图像的自主室内导航门检测

The 23rd IEEE International Symposium on Robot and Human Interactive Communication Pub Date : 2014-10-20 DOI:10.1109/ROMAN.2014.6926245

Yimin Zhou, Guolai Jiang, Guoqing Xu, Xinyu Wu, L. Krundel

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引用次数: 13

摘要

针对机器人自主路径规划问题，提出了一种室内导航算法。由于室内环境的复杂情况，机器人在巡逻时的路线识别会给机器人带来严重的麻烦，尤其是拐角和门的检测，这是智能导航的关键步骤。为了解决这个问题，使用kinect传感器通过深度图像进行门检测和角定位。分析了图像中连续变化的比例和深度差，用于角和门的识别。此外，可以通过深度图像的三维特征来定位门和角的精确位置。通过不同场景下的实验，验证了该算法在机器人室内自主导航中的有效性。

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Kinect depth image based door detection for autonomous indoor navigation

In this paper, an indoor navigation algorithm is proposed for the purpose of robot autonomous path planning. Due to the complex situation in indoor environments, it can cause a serious trouble for robot to identify the route during patrolling, especially for corner and door detection, which is the key step for intelligent navigation. To solve this problem, a kinect sensor is used for the door detection and corner location via depth images. The continuously varied ratios and depth difference in the images have been analyzed for the corner and door identification. Furthermore, the precise position of the doors and corners can be localized via the 3-dimensional characteristics of the depth images. Experiments in different scenarios have been performed to verify the efficacy of the algorithm for robot indoor autonomous navigation.

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The 23rd IEEE International Symposium on Robot and Human Interactive Communication

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