Autonomous positioning for wall climbing robots based on a combination of an external camera and a robot-mounted inertial measurement unit
ZHANG Wen, DING Yulin, CHEN Yonghua, SUN Zhenguo
Key Laboratory for Advanced Materials Processing Technology of Ministry of Education, Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China
Abstract：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.
张文, 丁雨林, 陈咏华, 孙振国. 基于外部视觉与机载IMU组合的爬壁机器人自主定位方法[J]. 清华大学学报（自然科学版）, 2022, 62(9): 1524-1531.
ZHANG Wen, DING Yulin, CHEN Yonghua, SUN Zhenguo. Autonomous positioning for wall climbing robots based on a combination of an external camera and a robot-mounted inertial measurement unit. Journal of Tsinghua University(Science and Technology), 2022, 62(9): 1524-1531.
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2022, Vol. 62 
