Jixie chuandong (Jan 2024)
End Pose Compensation System of Spraying Robots Based on Unscented Kalman Filter Algorithm
Abstract
The spraying construction robot is unable to include information about ground leveling in the map when it is created, and when the robot operates according to the built map, the spraying clamping fixture at the working end of the spraying construction robot can not be parallel to the wall due to the lack of ground information. In order to compensate the posture error of the spraying fixture relative to the wall, a multi-sensor fusion method is proposed based on the unscented Kalman filter to compensate the posture of the spraying fixture.The state equation of the fixture posture is constructed from the data measured by the displacement measurement sensor， the equation of fixture posture measurement is constructed from the data measured by the gyroscope, and the optimal estimation of the fixture posture is obtained by using the unscented Kalman filter algorithm and transferring them to the robot, so as to achieve the purpose of compensating the posture error of the spraying fixture. Finally, the experimental platform is built to verify the feasibility of the error compensation system. The experimental results show that the positional error between the spraying fixture and the wall after error compensation is reduced to 0.005°.
