Localization of Wall Climbing Robot on Cylinder-Shaped Steel

Abstract

Due to the limitation of sensor application in special environment such as relatively closed and magnetic interference environment, the positioning and the heading angle errors of wall climbing robots accumulate with time. This paper proposes a difference projection localization method based on an external RGB-D camera and a robot-carried inertial measurement unit (IMU). We differential the depth image to obtain the distance change due to the robot occupancy. Then, the 3D point cloud information is converted into 2D image information by projecting the above distances along the normal vector of the robot chassis, which greatly speeds up the computational speed. The position of the robot is calculated by studying the statistical characteristics of the projection. Two EKFs are designed to estimate the attitude, taking the gravity vector and the normal vector of the robot chassis as observation. The experimental results show that the localization error of the wall climbing robot is within 0.017m, and the heading angle error of the attitude estimation is within 3.1∘. The obtained results prove its applicability in self-localization of the wall climbing robot.