| Abstrakt: |
In the operations of maintenance for armored equipment, to achieve an automatic loading and unloading of some components of the vehicle chassis, the problem of automatically scanning for the unknown components of CAD model as well as the model reconstruction for free-form surfaces need to be solved. In this study, a surface reconstruction approach based on industrial robot non-contact adaptive measurement is proposed. In the process, a laser displacement sensor is installed on the flange of robot end-effector, and a coordinate transformation model is established. Then, based on the measured point on the component and the adaptive measurement algorithm of curve arc length extrapolation prediction, the next prediction vector is calculated and a B-spline fitting curve is generated. Ultimately, with rational planning of measurement path, this method can be applied for guiding industrial robotic arm to automatically collect real three-dimensional points on the component under test. The results of the simulation and experiment indicate that with this approach, the sampling points can be determined according to the surface features of components, and the detriment of precision due to the existence of incident angle as well as defects of the algorithm can be reduced. Thus, this approach improves the sampling accuracy of unknown free-form surface, and provides better point cloud data for model reconstruction. [ABSTRACT FROM AUTHOR] |
