A Method for Registration of 3-D Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Planning for complete sensor coverage in inspection
Computer Vision and Image Understanding
IVIS: an integrated volumetric inspection system
Computer Vision and Image Understanding
Automatic sensor placement for accurate dimensional inspection
Computer Vision and Image Understanding
Computing Occlusion-Free Viewpoints
IEEE Transactions on Pattern Analysis and Machine Intelligence
Autonomous Exploration: Driven by Uncertainty
IEEE Transactions on Pattern Analysis and Machine Intelligence
The NURBS book (2nd ed.)
Automated surface acquisition using range cameras
Automated surface acquisition using range cameras
Active modeling of 3-D objects: planning on the next best pose (NBP) for acquiring range images
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
Machine Vision and Applications
Active vision in robotic systems: A survey of recent developments
International Journal of Robotics Research
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The use of a laser range sensor in the 3D digitalization process allows significant improvement in acquisition speed and in 3D measurement point density. However, if we want to use these 3D data in applications that require data with a high degree of accuracy like inspection tasks, it is mandatory that the 3D points be acquired under the best conditions of accuracy. During 3D capture of a part, several sources of error can alter the measured values. Thus we must find and model the most important parameters affecting the accuracy of the range sensor. This error model, along with the CAD model of the part, is used to produce a sensing plan to completely and accurately acquire the geometry of the part. The sensing plan is comprised of the set of viewpoints that defines the exact position and orientation of the camera relative to the part. There is no limitation with regard to the shape of the part to be digitalized. An autosynchronized range sensor fixed on a coordinate measuring machine was used. For this sensor, the accuracy of the 3D measured points is a function of the distance and of the angle of incidence relative to the surface. The strategy proposed to find the acquisition plan guarantees that the viewpoints meet the best accuracy conditions in the scanning process, solving the occlusion problems. It was found that the 3D data acquired by using the proposed strategy are around 30% more accurate than the 3D data obtained in a standard acquisition.