A method for measuring the sculptured surface of rotation by using coordinatemeasuring machine (CMM) and rotary table is proposed. The measurement is realized during thecontinuous rotation of the workpiece mounted on ...A method for measuring the sculptured surface of rotation by using coordinatemeasuring machine (CMM) and rotary table is proposed. The measurement is realized during thecontinuous rotation of the workpiece mounted on the rotary table while the probe moves along thegeneratrix of the surface step by step. This method possesses lots of advantages such as simplicityof probe motion, high reliability and efficiency. Some key techniques including calibration of theeffective radius of the probing system, determination of the position of axis of rotation,auto-centering of the workpiece, data processing algorithm, are discussed. Approaches fordetermining the coordinates on measured surface, establishing workpiece coordinate system andsurface fitting are presented in detail. The method can be used with contact or non-contact probes.Some fragile ceramic and plaster parts are measured by using the system consisting of a CMM, rotarytable, motorized head and non-contact laser triangulation probe. The measuring uncertainty is about0.02 mm which meets the general requirement in most cases.展开更多
Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yie...Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yielded impressive achievements for spacecraft pose estimation.To improve the robustness and interpretability of CNNs,this paper proposes a Pose Estimation approach based on Variational Auto-Encoder structure(PE-VAE)and a Feature-Aided pose estimation approach based on Variational Auto-Encoder structure(FA-VAE),which aim to accurately estimate the 6 DoF pose of a target spacecraft.Both methods treat the pose vector as latent variables,employing an encoder-decoder network with a Variational Auto-Encoder(VAE)structure.To enhance the precision of pose estimation,PE-VAE uses the VAE structure to introduce reconstruction mechanism with the whole image.Furthermore,FA-VAE enforces feature shape constraints by exclusively reconstructing the segment of the target spacecraft with the desired shape.Comparative evaluation against leading methods on public datasets reveals similar accuracy with a threefold improvement in processing speed,showcasing the significant contribution of VAE structures to accuracy enhancement,and the additional benefit of incorporating global shape prior features.展开更多
文摘A method for measuring the sculptured surface of rotation by using coordinatemeasuring machine (CMM) and rotary table is proposed. The measurement is realized during thecontinuous rotation of the workpiece mounted on the rotary table while the probe moves along thegeneratrix of the surface step by step. This method possesses lots of advantages such as simplicityof probe motion, high reliability and efficiency. Some key techniques including calibration of theeffective radius of the probing system, determination of the position of axis of rotation,auto-centering of the workpiece, data processing algorithm, are discussed. Approaches fordetermining the coordinates on measured surface, establishing workpiece coordinate system andsurface fitting are presented in detail. The method can be used with contact or non-contact probes.Some fragile ceramic and plaster parts are measured by using the system consisting of a CMM, rotarytable, motorized head and non-contact laser triangulation probe. The measuring uncertainty is about0.02 mm which meets the general requirement in most cases.
基金supported by the National Natural Science Foundation of China(No.52272390)the Natural Science Foundation of Heilongjiang Province of China(No.YQ2022A009)the Shanghai Sailing Program,China(No.20YF1417300).
文摘Real-time 6 Degree-of-Freedom(DoF)pose estimation is of paramount importance for various on-orbit tasks.Benefiting from the development of deep learning,Convolutional Neural Networks(CNNs)in feature extraction has yielded impressive achievements for spacecraft pose estimation.To improve the robustness and interpretability of CNNs,this paper proposes a Pose Estimation approach based on Variational Auto-Encoder structure(PE-VAE)and a Feature-Aided pose estimation approach based on Variational Auto-Encoder structure(FA-VAE),which aim to accurately estimate the 6 DoF pose of a target spacecraft.Both methods treat the pose vector as latent variables,employing an encoder-decoder network with a Variational Auto-Encoder(VAE)structure.To enhance the precision of pose estimation,PE-VAE uses the VAE structure to introduce reconstruction mechanism with the whole image.Furthermore,FA-VAE enforces feature shape constraints by exclusively reconstructing the segment of the target spacecraft with the desired shape.Comparative evaluation against leading methods on public datasets reveals similar accuracy with a threefold improvement in processing speed,showcasing the significant contribution of VAE structures to accuracy enhancement,and the additional benefit of incorporating global shape prior features.
