MECHANICAL ENGINEERING |
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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 |
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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.
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Keywords
RGB-D cameras
3D point cloud
extended Kalman filters
wall climbing robots
inertial measurement unit
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Issue Date: 18 August 2022
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