Cylinder Detection From RGBD Data Based on Radius Estimation Using Number of Measurement Points

In this paper, we describe a method to estimate cylindrical parameters using RGBD data. As cylindrical shape is one of the shape elements that composes of a building, to know cylindrical parameters accurately is useful to robots aiming to grasp such part. Therefore, we propose a method to estimate the diameter and the inclination of a cylinder part. We formulate the relationship between cylinder diameter and the number of 3D points measured from the cylinder. It enables to estimate cylinder diameter from measured point cloud directly. Through proof experiments, we show that our method is more accurate than conventional methods. Moreover, as an example of the search activity at disaster environments, we report an experiment on grasping a ladder by an autonomous mobile manipulator and showed the effectiveness of the proposed method.