未知环境下地面的不平坦性和机器人相对障碍物位姿的不确定性会造成障碍物特征提取困难,为了准确检测障碍物特征,采用3维相机获取机器人周围环境的灰度图像和距离信息。在此基础上,提出基于灰度信息和3维信息的"阈值法"进行障碍物区域的提取,并针对3维信息"阈值法"剔除的地面与障碍物过渡区域过多,以及机器人相对斜坡方位的不确定性引起的障碍物特征检测不准确,提出区域的恢复算法和表面法线坡度计算。实验结果表明,所提出的算法具有简单、有效、准确和鲁棒性强的优点。

Because of the unevenness of terrain and the uncertainty of the position and orientation of a mobile robot,it is difficult to get the obstacle characteristics in unknown environments.In order to detect the obstacle characteristics accurately,a 3D camera is used to obtain a gray image and the depth information of the environment.Then a threshold method based on the obtained gray image and the 3D information is presented to determine the area of an obstacle.But inaccurate feature detections will still exist in the above 3D information threshold method,caused by different factors,for example,too much transition regions between the ground and the obstacle are eliminated or the relative position between the robot and the slope is uncertain.In order to solve these problems,a region recovery algorithm and a computation method of slope degree estimation are developed.Experimental results show that our algorithm has the merits of simplicity,effectiveness,accuracy and high robustness.