Autonomous positioning for wall climbing robots based on a combination of an external camera and a robot-mounted inertial measurement unit

被引：0
|
作者：
Zhang W. [1 ]
Ding Y. [1 ]
Chen Y. [1 ]
Sun Z. [1 ]
机构：
[1] Key Laboratory for Advanced Materials Processing Technology of Ministry of Education, Department of Mechanical Engineering, Tsinghua University, Beijing
来源：
Qinghua Daxue Xuebao/Journal of Tsinghua University | 2022年 / 62卷 / 09期
关键词：
3D point cloud; extended Kalman filters; inertial measurement unit; RGB-D cameras; wall climbing robots;
D O I：
10.16511/j.cnki.qhdxxb.2022.26.009
中图分类号：
学科分类号：
摘要：
Sensor accuracy in special environments can be very limited due to closed systems and magnetic interference. For example, sensors on wall climbing robots can experience accumulation of autonomous positioning errors with time. The paper presents an autonomous positioning method for wall climbing robots based on an external RGB-D camera and a robot-mounted inertial measurement unit (IMU). This method uses the target tracking method with a deep learning and kernelized correlation filter (KCF) for preliminary positioning. A normal direction projection method is then used to locate the center on the top of the robot shell for the robot position positioning. The system determines the normal, the roll angle and the heading of the robot with a series EKF filter calculating the roll angle, pitch angle and heading to estimate the robot attitude. Tests show that the wall climbing robot positioning error is within 0. 02 m. the heading error and the roll angle error for the attitude estimate are both within 2.5% and the pitch angle error is within 1.5°. This system effectively improves the wall climbing robot positioning accuracy. © 2022 Press of Tsinghua University. All rights reserved.
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页码：1524 / 1531
页数：7
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