Perception Algorithm of Position and Attitude for Self-Driving Rollers

The accurate perception of pose information can help in solving the problem of the substandard control accuracy of self-driving rollers. This paper aims to improve the perception results of self-driving rollers in a complex environment and solve the problem of the poor accuracy and universality of the existing posture perception algorithms. To realize this, a joint algorithm framework for the position measurement and heading measurement of the self-driving roller is proposed. First, to improve the positioning accuracy of the self-driving roller in complex environments, a kinematics prediction equation is constructed based on the attitude and heading reference system(AHRS)accelerometer data and gyroscope data, and GPS data and a set of constraint matrices of velocity are used to construct a measurement equation. Based on prediction equation and measurement equation, an extended Kalman filter-based loosely coupled algorithm is designed to calculate more accurate coordinates. Second, to solve the inconsistency of the front and rear bodies heading angle caused by the articulated structure of the roller, an empirical equation for estimating the heading angle is constructed by analyzing the principle of the AHRS output magnetic azimuth and the output data;then the variables in the equation are calibrated by the backpropagation(BP)neural network model. Finally, an experimental verification of the perception algorithm of the attitude and position is conducted on the modified intelligent roller platform. The experimental results show that when the self-driving roller relying only on GPS has measurement deviations due to road fluctuations, the algorithm effectively compensates for the deviations. When the GPS failed for 3s, the root-mean-square error between the output value of the system and the real value was 10.9cm. At low speed, the maximum error between the output heading angle and the GPS measurement was 0.45°, which effectively solves the problem of measuring the heading angle of the rear body. The result shows that the perception system exhibits better accuracy and effectiveness. © 2021, Editorial Board of Journal of Tianjin University(Science and Technology). All right reserved.