No abstract

To overcome the problem of the low accuracy and large accumulated errors of indoor mobile navigation and positioning, a method to integrate the light detection and ranging-and inertial measurement unit-based measurement is proposed. Firstly, the voxel-scale-invariant feature transform feature extraction algorithm for light detection and ranging is studied. Then, the errors of light detection and ranging measurement due to the change of the scan plane compensated based on aiding information from inertial measurement unit. The relative position parameters and the differences of measurements of light detection and ranging at adjacent times are used to estimate the error of inertial measurement unit sensors by a Kalman filter. Several experiments are carried out in the indoor corridor and the results demonstrate that precision of the light detection and ranging/inertial measurement unit-integrated indoor mobile robot localization is higher than that of single light detection and ranging sensor.