Visual Measurement Method and Application of Mobile Manipulator Pose Estimation Based on PPMCC-IMM Filtering

Increasing demand for mobile manipulators in fields requiring high-precision tasks has introduced new requirements regarding their kinematic accuracy. Pose measurement of the mobile manipulator is a crucial method to improve the absolute positioning accuracy of the robot. To solve the pose estimation of the mobile manipulator, we propose a space measurement method based on visual marks and an interactive filtering method to improve the stability of measurement results. First, the kinematics and dynamics of the mobile manipulator are analyzed, and the mathematical expression of the model is obtained to obtain the theoretical trajectory. Second, a visual marker based on pyramid hierarchy is proposed, which can adapt to scenes with significant distance scale changes. A visual marker of a regular 12-face is designed, the marker of each face is uniquely coded to ensure that multiple markers can be captured at the same time under a single viewing angle, and geometric relations determine the distance and pose of the end. We propose a filtering method considering the correlation of historical data to improve the stability and accuracy of measurement data. The matching degree of the filter motion mode is improved through the Pearson coefficient relationship between the filtered data in the current period and the historical data. In this article, several experiments verify the method's effectiveness. The repeatability of the measurement can reach 0.75 mm, and the mean error (MAV) is 0.009 mm. The noise test proves the anti-interference ability of the filtering method. The new filtering method has excellent performance on various tracking tracks. All experiments show that the method proposed in this article has a good measurement effect and is a low-cost, convenient, and efficient method to solve the pose estimation and precise trajectory error analysis of mobile manipulators.