A Method for Estimating Heading Angle of Mobile Robot

Abstract

The invention discloses a method for estimating a course angle of a mobile robot. The method comprises the following steps: utilizing a gyroscope to detect a course angular velocity of the mobile robot, and utilizing a magnetometer to detect the course angle of the mobile robot; utilizing a state augmentation method to establish a course angle state space model; and utilizing anti-deviation self-correcting kalman filtering to perform data fusion, thereby acquiring the optimal estimation for the course angle. Compared with the prior art, the method has the advantages that 1) a drift error of the gyroscope can be effectively compensated, and meanwhile, the magnetometer is utilized to eliminate the accumulated error of the course angle estimation; 2) the filter coefficient is changed following the change of a sensor noise, and the estimation precision is further promoted; and 3) a fault magnetometer reading result can be recognized and isolated, and the estimation reliability can be further promoted.

Description

technical field [0001] The invention relates to the technical field of robots, in particular to a heading angle estimation method of a mobile robot. Background technique [0002] Mobile robot is a comprehensive system integrating environment perception, dynamic decision-making and planning, behavior control and execution. With the continuous improvement of robot performance, the application range of mobile robots has been greatly expanded. It is well applied in dangerous situations. Therefore, mobile robot technology has received widespread attention from all over the world. [0003] Accurate detection of the heading angle of a mobile robot is the prerequisite for its route planning, navigation and obstacle avoidance. The traditional method has the following problems: 1) There is a cumulative error in the gyroscope or encoder-based heading angle estimation method, and the error becomes larger and larger as time goes by; 2) Although the heading angle detection method based...

AI Technical Summary

Problems solved by technology

The traditional method has the following problems: 1) There is a cumulative error in the gyroscope or encoder-based heading angle estimation method, and the error becomes larger and larger as time goes by; 2) Although the heading angle detection method based on the magnetometer does not have Cumulative error, but its accuracy will be affected by ferromagnetic substances in the environment, so there is a large uncertainty

However, their common shortcoming is that they do not consider the variation of sensor noise and the failure of magnetometer

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