摘要： 自主移动机器人的导航要求能实时规避障碍物。为解决该问题，提出一种基于光流的自主移动机器人避障系统。将机器人在运动过程中通过摄像头拍摄的连续图像序列作为输入，使用金字塔Lucas-Kanade方法在角点处提取光流信息求解延伸焦点和接近时间，并通过改进的平衡策略估计障碍物可能存在的位置。实验结果表明，该系统在静态场景中能正确地检测并规避宽度大于10 cm，且不完全遮挡摄像头视角的障碍物，可行性较高。
关键词:
光流,
避障,
平衡策略,
延伸焦点,
接近时间,
移动机器人
Abstract: Since real-time obstacle avoidance is a key part of mobile robot autonomous navigation, an autonomous mobile robot obstacle avoidance system based on optical flow is proposed. This system’s input is the image sequence grabbed by the camera on the robot in motion. The optical flow information is extracted by Pyramid Lucas-Kanade method to calculate focus of expansion and time to contact. The possible position of the obstacle is estimated with improved balance strategy. Experimental results show that this system can detect and avoid obstacles with the width larger than 10 centimeters but not cover the camera view correctly, which validates the method’s feasibility.
Key words:
optical flow,
obstacle avoidance,
balance strategy,
focus of expansion,
time to contact,
mobile robot
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