移动机器人障碍物检测是机器人避障和移动路径规划的基础，为了提高视觉机器人障碍物检测能力，尤其是障碍物识别能力，针对传统的灰度图像分割作为障碍物目标识别方法在某些环境下效果不佳的问题，提出一种基于彩色图像分割的障碍物检测方法。首先充分利用 HSI 颜色模型中各个颜色分量的特征，再结合 Otsu 自适应阈值方法进行对应空间的图像阈值分割。考虑到机器人工作环境下外界光照条件变化较大的特点，提出了对亮度空间 I 进行非线性指数变换处理的做法，以解决图像分割和障碍物识别易受光照变化影响的问题。实验结果证明了该方法的可行性和有效性，可为障碍物检测提供清晰准确的障碍物识别结果。%Mobile robot obstacle detection is the basis of robot obstacle avoidance and mobile path planning. In order to improve the detection ability of the obstacle detection in the visual robot, especially the obstacle recognition ability,aiming at the problem of the traditional gray image segmentation as an obstacle to the target recognition method in some environment,a method for the detection of obstacle detection based on color image segmentation was proposed. Firstly, the characteristics of each color component in the HSI color model were fully utilized,and the image threshold segmentation based on the Otsu adaptive threshold method was applied. In addition, considering the change of the environment of the robot working environment,the changes of the illumination conditions are relatively large,we proposed a method to deal with the nonlinear exponential transformation of the luminance space I in order to improve the image segmentation and obstacle recognition,and the problem is easily affected by illumination changes. Experimental results demonstrate the feasibility and effectiveness of the proposed method and it can provide clear and accurate obstacle recognition result for obstacle detection.
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