A Two-Stage Local Positioning Method With Misalignment Calibration for Robotic Structural Monitoring of Buildings

In structural health monitoring (SHM) applications carried out by mobile robots, the precise locating of the SHM robot is essential for accurate detection and quantification of defects. The traditional dead reckoning (DR) approach can only provide local position in the horizon, which is not enough for SHM applications in three dimensions in large buildings. In this paper, a new robot positioning algorithm for active building structural defect detection and localization is proposed. The two-stage robot positioning scheme is designed through the self-misalignment calibration and the positioning during SHM task stages, fusing the absolute and relative measurements. In order to overcome the drawback of the DR algorithm, in the full analysis of existing localization mode that can be applied to mobile robots, this paper adopted the inertial navigation system (INS) approach to measure the absolute motion information of a moving robot. On this basis, through the transformation between the absolute positioning coordinates and the local positioning coordinates of buildings, the mobile robot's optimal trajectory on building surface was designed for self-calibration of coordinate misalignments. The proposed method could effectively achieve the robot local positioning in building coordinate frame by fusing the external relative assistant measurements with absolute measurement. By using the designed strategies, the coordinate misalignment can also be self-calibrated effectively, improving local positioning accuracy.